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'All INdiana Politics': Cost of living and AI regulation dominate Indiana’s most competitive House race
INDIANAPOLIS — The race for Indiana’s 5th Congressional District has emerged as the state’s most competitive contest as Democratic State Sen. JD Ford challenges Republican incumbent Rep. Victoria Spartz. The district, which includes Hamilton, Tipton, Howard, Grant, Madison, and Delaware counties, has historically served as a Republican stronghold. However, shifting trends in the northern Indianapolis […]
BYU Beats Iowa State, Sets up Notre Dame Matchup
BYU dominated the stat sheet, but some miscues kept BYU from really controlling the game in a 24-10 home win over Iowa State Friday night in Provo. In a night where BYU needed their QB to carry them, Bear Bachmeier dominated with 329 passing yards, 2 passing TDs, and 109 rushing yards on 9 carries. […]
The Houston Rockets Dominate in their First Preseason Game
The Rockets defeat the Mavericks 135–117. Houston put up a nearly flawless performance on both ends of the court.
Dodgers tap NLCS rotation order to replicate dominance over Brewers
Dodgers pitching dominated the Brewers in last year's NLCS. They are hoping Tarik Skubal and Yoshinobu Yamamoto can set a similar tone in this year's rematch
Four Tigers Rookies Break Into MLB’s Top 50
Led by Kevin McGonigle’s top-ranked campaign, Detroit’s rising stars dominated the 2026 rankings, signaling a powerful youth movement and a bright future for the rebuilding franchise’s core.
NVIDIA-Backed Upscale Wants to Make Rival AI Chips Work Together
NVIDIA GPUs dominate today’s AI data centers, but they’re no longer the only processors companies want to use. Cloud providers are developing their own AI chips, while specialized accelerators are entering the market. Getting these different processors to work together efficiently is creating a new challenge for data center operators. That’s the problem Upscale hopes […]
Inside Broward County’s battle for health care real estate
Broward County’s health care giants are racing to snap up real estate, competing for space amid rapid population growth and development. The county’s health care map, long dominated by a neatly defined duopoly between taxpayer funded hospital districts Broward Health and Memorial Healthcare System, is changing as an outpatient construction boom floods the market with new facilities and health care systems look beyond traditional medical real estate to expand their portfolios. But with prime development sites growing scarce, the county has emerged as a medical development battleground, with systems jockeying for land, market share and the opportunity to redraw the […]
5 Key Moments From Hostile Michigan Senate Debate Between El-Sayed and Rogers
Slashing personal attacks dominated the first televised face-off between Dr. Abdul El-Sayed, the Democratic nominee for Senate, and former Representative Mike Rogers, his Republican rival.
Cost Concerns Dominate as Public’s Economic Ratings Turn More Negative
The costs of many household essentials are a top economic concern for most Americans – much as they were four years ago on the eve of the last midterm election.
Biggest Titans Weaknesses Texans Need to Exploit in Week 5
The Texans can dominate Week 5 by pressuring the Titans’ struggling pass protection and capitalizing on costly offensive mistakes
Republican megadonors dominate 2026 midterm election as crypto and AI money surges, CNBC analysis finds
Fourteen of the 20 biggest donor groups CNBC analyzed are Republican-aligned as crypto, AI and betting money reshapes 2026 midterm spending.
Bosnia’s political future looks increasingly like its past
Three nationalist parties are poised to dominate again, deepening fears of division and paralysis.
Thunder Rookie Aday Mara Passed His First Real Test
The 7-foot-3 Spaniard dominated the paint against Pelicans starters, flashing elite versatility and rim protection that suggests the Thunder have unearthed another high-impact piece for their frontcourt.
National high school girls soccer composite rankings
Indiana continues to dominate the latest USA TODAY Sports composite rankings for high school girls soccer this fall.
1 Smart Business Story: How Founders Use PR To Dominate
Media is a minefield. From Substacks and livestreams to podcasts and newspapers (where they still exist), it’s a lot for founders to juggle. Fortunately,
Brazil: Lessons from a Disaster
By Antonio Martins (Outras Palavras) Defeats become deeper and more prolonged when we misunderstand what caused them, avoid correcting course, and embrace “solutions” that only compound our mistakes. Lula’s government and the Brazilian left suffered a disaster in Sunday’s election. Contrary to every poll, the president finished the first round 2.2 million votes behind Flávio Bolsonaro—and, more significantly, 3.4 million votes below his total four years ago, when the machinery of the state was working against him and in favor of his opponent. His vote share declined in 98 percent of Brazil’s municipalities. The PL, the main party of the far right, elected 121 deputies and 28 senators, becoming the largest caucus in both houses of Congress. The parties aligned with the Centrão—Brazil’s bloc of transactional center-right parties—were somewhat diminished, but will still hold roughly 250 seats in the Chamber of Deputies and 35 in the Senate. That will make it easier to assemble the majorities needed to amend the Constitution or impeach Supreme Federal Court justices. If elected, Flávio Bolsonaro could appoint four members of the Court, substantially altering its internal balance of power. What produced these results? How can the far right be prevented from consolidating them into a prolonged political hegemony? And what is the essential change of direction the left now needs? Explaining the Disaster Across the commercial media and the exuberant chaos of digital platforms, interpretations are multiplying. Some focus on specific episodes: Lula’s absence from the Globo debate, his very close relationship with Alexandre de Moraes, or his emphasis on issues supposedly remote from most people’s everyday concerns, such as rare earth minerals. Among the more systemic interpretations, three seem especially questionable. One argues that the principal defeat was not the left’s, since its congressional representation declined only slightly. The decisive movement captured at the ballot box, according to this view, was a shift within the right itself—from the more moderate and transactional forces of the Centrão toward the more ideological and radicalized forces of the PL and Novo. A second interpretation holds that the nature of electoral and political processes has changed. The material interests and aspirations of society, it argues, no longer play the central role they once did; they have given way to forms of subjective self-identification that the left has yet to understand. And a third concludes that, because of these two developments, we should expect a political winter: a prolonged period in which the far right and the broader right dominate Brazilian political life. There are important elements in all three interpretations. The problem lies in what they deny or leave out: Lula’s third government was a small-bore government. It offered the majorities that elected it neither a clearly better life nor reasons to believe again in politics and its power to transform society. These failures flowed from two fatal accommodations, which I will examine below. As a result, the government suffered a slow but steady erosion of support. And, as has happened in so many Western countries, it gave the far right the opportunity to present itself as anti-system and to benefit from popular frustration and distress. The interpretation that emphasizes the migration of votes from the center-right and traditional right toward the far right has been advanced, among others, by the courageous journalist Leonardo Sakamoto. In his UOL column on Monday, October 5, he highlights the miserable behavior of the traditional conservative parties. Over the past four years, they repeatedly joined forces with the “neo”-fascists, helping to “normalize” them—a criticism that could equally be directed at almost the entire corporate media. Believing they could use the far right as a stepping stone, they instead ended up partly devoured by it. This was especially true in the Senate, where the PL’s gain of 13 senators and Novo’s gain of two came at the expense of the PSD, which lost nine; the MDB, which lost two; the PSDB, which lost two; and the PP, which lost one. Sakamoto’s observation is accurate and necessary, but it leaves uncomfortable questions unanswered. Why did the erosion of the Centrão benefit the far right rather than, for example, producing growth for the left—as has happened so many times before, both in Brazil and elsewhere? The answer is not difficult. Throughout its four years in office, Lula’s third government was almost invariably associated with the Centrão. Here lies its first accommodation: accepting the limits imposed by conservative institutions; avoiding, as much as possible, any attempt to strain those limits through popular pressure; and believing only in the modest changes that could be squeezed through openings in Congress. The failure of the campaign to end the six-day workweek is emblematic. Lula could have electrified the presidential race by pairing it with a popular campaign for passage of the measure. Instead, he chose to place his hopes in the hands of Senate president Rodrigo Alcolumbre. He generated no mass mobilization, did not force his opponents onto an uncomfortable defensive, and won no victory. In September 2025, the government squandered the greatest of its many opportunities to shake up conservative power in Congress. Popular opposition to the so-called Shielding Amendment—which, if approved, would have restricted criminal proceedings against members of Congress—brought crowds into the streets, mobilized primarily by artists and social movements. This opened the possibility for a broader political education: a campaign that could begin exposing the limits and dysfunctions of Brazil’s political system while putting Bolsonaro’s movement on the defensive for its predictable support of political privilege. The amendment was defeated. But the executive branch then backed away from the fight. It remained associated with an institutional world widely seen as corrupt, elitist, and indifferent to ordinary people’s struggles. In doing so, it forfeited its credibility as a vehicle for the protest vote. On Sunday, it reaped the bitter fruits. Are We Doomed? Taking a different approach from Sakamoto, the philosopher Moysés Pinto Neto and other writers have drawn attention, in their first analyses of October 4, to the fragmentation of the public sphere produced by Big Tech platforms. Through their algorithms, these platforms present each person with a different view of social reality. As a consequence, it becomes much harder to identify common material problems and demands—for example, the fight for labor rights or for a properly funded public health system. Voters no longer embrace such demands, these authors argue, because they no longer see themselves as part of a collective. Instead, they tend to value the identities assigned to them by neoliberal subjectivity—the role of the entrepreneur, for example. On this interpretation, the left’s possible error lies in clinging to outdated illusions. Moysés’s warning is highly relevant and resonates with arguments such as Naomi Klein and Astra Taylor’s “Apocalyptic Fascism and the Billionaires’ Bet.” Unlike a century ago, the far right no longer promises a radiant future. It concentrates instead on resentment—especially that of young men. “They belong to a generation that fears it may never own a home, but compensates with the pleasure it gets from constantly provoking progressives online. Convinced their future has been stolen, they share memes romanticizing historical authoritarian regimes,” the authors write. But Moysés seems to confuse this danger with inevitability. He fails to see that the left’s answer cannot be adaptation. On the contrary, it must strengthen the possibility of politics as collective action. Nor does he recognize that precisely such a reversal is already becoming possible in some of the most promising mobilizations of the twenty-first century: the election, at the end of 2025, of the young Muslim Zohran Mamdani as mayor of New York, on a platform centered on the intensely material fight for an affordable city; the Left Party’s victory in Berlin two weeks ago, built around the demand to expropriate private real-estate corporations; and the very recent wave of demonstrations in Spain—including an occupation of Madrid’s Puerta del Sol—in which tens of thousands of young people mobilized by the Tenants’ Union have demanded limits on rents. By putting itself in the straitjacket of the “fiscal framework” in the first months of 2022, Lula’s third government adopted the second fatal accommodation of its term. Faced with conservative institutions and a country devastated by four years of Bolsonaro, increased public investment was the government’s remaining weapon for offering a more dignified life to the majority and forging an anti-conservative pact with them. The same state that disburses 1 trillion reais a year to enrich a small class of rentiers could instead spend money to extend the Family Health Strategy to every Brazilian, at a cost of 30 billion reais; provide full-day public schooling and childcare to all adolescents and children—and, especially, relief to their mothers; achieve universal sanitation while cleaning up polluted urban rivers; multiply metro systems; begin transforming the urban peripheries; and undertake many other urgently needed projects. In April 2023, an article in Outras Palavras warned that the fiscal framework could “shrink the Lula government and preserve the forces that condemn the country to inequality and regression.” A year later, another article showed that restraints on public spending were strangling policies vital to ordinary people and undermining the president’s popularity. In November 2024 came a reality check, in the form of the government’s humiliating defeat in the municipal elections. Even then, the fiscal lock was neither removed nor loosened. On the contrary: throughout the government’s four years, fiscal restraint remained central to its political narrative. The administration proudly proclaimed that it had “put the state’s accounts in order,” without grasping either how misleading that phrase was—given the payment of 1 trillion reais in interest—or how badly the message was hurting it politically. Lula finally woke up in September 2026. The increase in Bolsa Família benefits, after four years of being frozen; the announcement that anti-obesity drugs would be offered through Brazil’s public health system; and the ban on online betting showed that the state has the power to act decisively on behalf of the majority when those in government are willing to confront obstacles. The huge marches that closed the campaign in Fortaleza, Salvador, Rio de Janeiro, and São Paulo on the eve of October 4 showed how such initiatives can mobilize activists and the broader public. But it was too late—and too little to change the outcome of the first round. History has not ended The possibility of a turnaround in the three weeks leading up to November 25 cannot be ruled out. It will not be simple or easy. Lula must not only make up a deficit of 2.2 million votes; he must also offset the movement of voters who backed other right-wing candidates in the first round, most of whom are likely to move toward Flávio Bolsonaro. Pulling that off will require a broad, grassroots effort to win over voters, potentially reinforced by new initiatives from Lula. The coming hours and days will be decisive. If Bolsonaro’s movement also wins the presidency, the result will create a high-risk situation for Brazilian sovereignty and democracy. The enormous challenges posed by such an outcome would require the left to reexamine, in depth and with a genuine willingness to engage in self-criticism, its political projects—or its lack of them—and its practices. But would that mean we are condemned to the long winter of far-right hegemony that some analyses are beginning to forecast? It is far too early to say, suggests a recent text by Álvaro García Linera, the thinker who served as vice president of Bolivia under Evo Morales. His central hypothesis is that this political current will prove short-lived. At a moment when the entire world is once again talking about sovereignty and protecting national economies, the far right offers a stale, recolonizing neoliberalism. Its submission to the United States is as blatant and pathetic as Flávio and Eduardo Bolsonaro’s overtures to Donald Trump. Its project amounts to something like every man for himself: greater inequality, capitalism without limits, devastation, and supremacism. Will it work? In the United States, just two years into his second term, Trump himself is reaching record levels of unpopularity and may be on the verge of losing Republican control of both the House and Senate in November. Every new beginning is difficult. Whatever the outcome of the second round, the defeats of October 4 show how profoundly the Brazilian left will have to rethink and rebuild. But just as it would be foolish to underestimate the seriousness of its mistakes, it would be equally foolish to conclude that rebuilding a political project is no longer possible. History has not ended. The times are moving faster than ever. Originally published in Portuguese by Outras Palavras. English translation by Eric Blanc; I’ve added the subtitles. More We can’t stop the far right at home or abroad without a revitalized labor movement, which is yet another reason why you should become a sustaining supporter of the Emergency Workplace Organizing Committee (EWOC) — one of US labor’s pivotal bright spots. Relatedly, Jacobin published a short piece of mine reflecting on a decade of Bernie Sanders inspiring a whole new generation of young worker organizers.
Spain's housing crisis bursts into the spotlight at snap election
Spain's snap election will revolve around an issue which has topped voters' list of concerns for three years straight but, until a fortnight ago, failed to dominate the political debate: housing.
Layla Zaidane: The politicians who can fix America’s polarization problem will win
Political predictions are notoriously unreliable, but here is one I am willing to stand behind: the elected officials who figure out how to govern across difference will dominate the next decade of American politics. With dysfunction and paralysis having become the status quo in Washington, elected officials who work together
Small Businesses Skip the Cross-Border Plumbing Big Companies Can’t Escape
Conventional wisdom says large corporations should dominate cross-border payments. They have global banks, treasury teams, negotiated FX rates,
Luke Fickell's 'vision' starting to show, Joe Thomas says
After the Wisconsin Badgers dominated Michigan State on Saturday, Hall of Famer Joe Thomas broke down the team's progress.
Science in French? Bien sûr!
As English dominates the publication landscape, support for French-language research is a strategic investment in the quality, equity and the future of knowledge.
Kalen DeBoer Has Bold Comments After Alabama Dominates Mississippi State
Alabama head coach Kalen DeBoer had some strong comments after his team dominated Mississippi State.
KIII 3 News
KIII 3NEWS is the ABC affiliate in Corpus Christi, Texas, operating to serve, inform and improve communities in the Coastal Bend. The station began broadcasting in South Texas on May 4, 1964. Today, KIII 3NEWS dominates one of the fastest-growing markets in Texas. The station’s service to the community and commitment to local news and weather coverage has consistently made it the Coastal Bend's news leader for decades.
Ohio State Dominates Iowa In Record-Breaking Fashion
Ohio State returned to Kinnick Stadium for the first time since the 2017 beatdown, and it went significantly better this time around. For as frustrating as all three phases were for the Buckeyes, Ohio State was in control from the jump, only allowing a late touchdown when the game was well in hand. In the …
Notre Dame dominated the trenches to take down UNC
The Heels hung around with one of the best teams in the country, but ultimately the Irish came away with the W.
TENNESSEE LADY VOLS VOLLEYBALL: Gators dominate in three sets
No. 11 Tennessee volleyball dropped a three-set match on the road against No. 7 Florida (22-25, 18-25, 23-25) on Friday evening.
HIGHLIGHTS: Somerset Academy (NV) vs. Midland Lee
MIDLAND, Texas (KMID/KPEJ) – Midland Lee dominated Somerset Academy from Nevada 61-6 as the Rebels improved to 4-2. Next week the Rebels kick off district play at home against Permian. Watch the video above for the highlights.
FNF Week 5: Jesuit dominates Holy Cross, 33-6
The Holy Cross Crusaders took on the Jesuit Blue Jays on Friday night at Tad Gormley Stadium.
Upper Dauphin dominates Camp Hill
(WHTM) — Camp Hill is looking to get their first win of the year as they take on Upper Dauphin in week six. Well, Camp Hill will have to try next week to get their first win as they lost 41-6. Meanwhile, Upper Dauphin improves to 3-3.
No. 3 Spartans Dominate Exhibition: The Eric Nilson Show
Eric Nilson’s four-point explosion and Joshua Ravensbergen’s poised debut fueled a surgical offensive display as the Spartans dismantled Boston College to signal their pursuit of another title.
Texas A&M Looks To Extend Arkansas Dominance At Kyle Field
Texas A&M returns home trying to stop a two-game skid and beat Arkansas for a fifth straight time in a rivalry the Aggies have dominated since 2012.
National high school girls soccer composite rankings
Indiana teams dominate the latest USA TODAY Sports composite rankings for high school girls soccer this fall.
Israeli Politicians Trade Barbs Over FlyDubai Attack
Prime Minister Benjamin Netanyahu’s campaign for a coming election was already dominated by discussion of the policy, military and intelligence failures leading up to the Hamas-led attacks on Oct. 7, 2023.
KIII 3 News
KIII 3NEWS is the ABC affiliate in Corpus Christi, Texas, operating to serve, inform and improve communities in the Coastal Bend. The station began broadcasting in South Texas on May 4, 1964. Today, KIII 3NEWS dominates one of the fastest-growing markets in Texas. The station’s service to the community and commitment to local news and weather coverage has consistently made it the Coastal Bend's news leader for decades.
Maine Democrat who rejects special interests previously ran PAC that courted them
Troy Jackson is challenging Republican Sen. Susan Collins in a pivotal contest that has been dominated by campaign finance issues.
Liverpool Could Trigger €70m Jarell Quansah Clause
The Reds face a high-stakes decision as their academy graduate dominates the Bundesliga, with a strategic buy-back clause offering a cut-price path to an Anfield homecoming.
Why Paolo Banchero is Ready to 'Dominate Every Single Night'
Armed with elite conditioning and a refined interior presence, Orlando’s cornerstone enters his third season hunting consistency and a superstar leap to lead the Magic through the East.
ChatGPT ads are dominated by business software companies so far
ChatGPT ads skew heavily toward business software, and there are bright points for the business, according to a new report from the agency Graphite.
Brandon McGinley: How being a one-party town warps Pittsburgh’s politics
Every time I write something critical about governance in Pittsburgh and Allegheny County, one response tends to predominate in the comments and emails: “This...
Beyond executive politics: Why football’s grassroots are betting on continuity
While political debates dominate football’s power centres, local member associations care about one primary goal: sustainable development on home soil. For many smaller federations, FIFA's support o...
Beyond executive politics: Why football’s grassroots are betting on continuity
While political debates dominate football’s power centres, local member associations care about one primary goal: sustainable development on home soil. For many smaller federations, FIFA's support o...
“I Was Struggling”: Myles Garrett’s GF Chloe Kim Reveals Health Diagnosis After Years of Suffering
Cleveland Browns star Myles Garrett dominates on the field, but off it, his girlfriend Chloe Kim has been fighting a very quiet battle. The two-time Olympic snowboarding champion opened up about a condition she lived with for years without fully understanding it.
Case Keenum Shines as Bears Dominate Eagles in Statement Win!
The Chicago Bears delivered one of their biggest performances of the young season Monday night, taking down the Philadelphia Eagles 27-7 at Soldier Field. With starting quarterback Caleb Williams sidelined by a hamstring injury, Chicago turned to veteran Case Keenum, and the longtime NFL quarterback delivered when his team needed him most. Keenum threw for…
For the Third Straight Week, Former Buckeyes Dominate the NFL
For the third straight week, one of the main storylines from the NFL is the former Buckeyes dominating at the next level.
No. 1 Texas outlasts No. 14 Tennessee 20-17 in Knoxville with Trump watching
Texas dominated defensively with 10 sacks, led by Colin Simmons.
Democrats keep coming to South Carolina to stump for midterm candidates. It's all about 2028
Democrats are flocking to South Carolina to campaign for midterm candidates, even though Republicans dominate state politics.
Democrats Keep Coming to South Carolina to Stump for Midterm Candidates. It's All About 2028
COLUMBIA, S.C. (AP) — On paper, South Carolina might be an odd place for Democrats to converge to campaign for midterm candidates. Republicans dominate state politics, and there's slim chance of that changing this year. But South Carolina is also the first state in Democrats' next presidential ...
Corn Nation Overreaction: Huskers Dominate Spartans, Remain Undefeated
Nebraska moved to 4-0 with a convincing 31-13 road victory over Michigan State, and Greg and Jake broke down an “ugly win” that still showed how far the Huskers have come. Nebraska didn’t play its best football, particularly in the running game, but the defense dominated with six sacks, multiple takeaways, excellent tackling, and impressive […]
‘All INdiana Politics’: Property tax reform and childcare costs dominate debate in key State Senate race
INDIANAPOLIS — The race for Indiana’s 29th State Senate district has emerged as a focal point for the upcoming elections as candidates compete for an open seat in a key swing district. The vacancy follows State Senator J.D. Ford’s decision to challenge U.S. Representative Victoria Spartz for her seat in Congress. The 29th District stretches […]
MTV VMAs 2026 Winners List: Madonna Dominates, Taylor Swift Wins Special Honor
It was like 1998 all over again. Madonna won six Video Music Awards that year for Ray of Light. Flash forward to tonight, and the pop icon won seven awards, including Artist of the Year, for Confessio...
Misiorowski Guides Brewers to 103rd Win in Regular Season Finale
Cy Young favorite Jacob Misiorowski dominated St. Louis, securing Milwaukee’s 103rd victory and a first-round postseason bye as Brice Turang eclipsed the 100-RBI milestone in the finale.
‘All INdiana Politics’: Property tax reform and childcare costs dominate debate in key State Senate race
INDIANAPOLIS — The race for Indiana’s 29th State Senate district has emerged as a focal point for the upcoming elections as candidates compete for an open seat in a key swing district. The vacancy follows State Senator J.D. Ford’s decision to challenge U.S. Representative Victoria Spartz for her seat in Congress. The 29th District stretches […]
Film Review: Miami Hurricanes 52
The Miami Hurricanes dominated the CMU Chips 52-3 at Hard Rock as a tune-up before Clemson in Death Valley.
No. 6 UM Dominates Central Michigan Behind Battle-Tested Depth
Darian Mensah makes FBS history and Chris Wheatley-Humphrey flashes explosive potential as the Miami Hurricanes’ relentless roster depth fuels a blowout victory ahead of high-stakes ACC play.
Seminoles WR Boggs Has Breakout Game vs. Central Arkansas
Sophomore Jayvan Boggs dominated Central Arkansas, racking up 122 yards and a long touchdown to solidify his role as a premier playmaker in the Seminoles' crowded offense.
UCLA dominates in all phases of the game during rout of Maryland
Bob Chesney became the first UCLA coach to start his tenure 4-0 since 1949, steering the Bruins to a 54-3 Big Ten road victory over Maryland Saturday.
Intel Panther Lake Teardown, 18A, BSPD, GAAFET, SemiAnalysis STEEL
Panther Lake debuts the first commercial implementation of backside power delivery (BSPDN), introduces Intel’s first iteration of gate-all-around (GAA) transistors, and showcases their advanced packaging capabilities with its Foveros-S assembly. With Panther Lake, Intel’s manufacturing arc has shifted from nebulous roadmaps to shipped silicon, a significant milestone on their long road back to competitive semiconductor manufacturing. To evaluate the extent of Intel’s comeback, we tore down Panther Lake. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Our teardown traces 18A from its four-sheet RibbonFETs (Intel’s marketing name for GAAFETs) and gate stacks through contacts, frontside and backside wiring, and the bonded carrier. We explain how these material and integration choices improve gate control and reduce resistance, while adding capacitance, thermal resistance, and process complexity. Our measurements put Panther Lake’s 18A compute logic and TSMC N3E GPU logic at similar logic density. However, 18A does not lead TSMC N3P, N2 or Samsung SF2 in peak density. Panther Lake’s CPU cores are incremental updates, and the high-end GPU still uses TSMC N3E. Panther Lake assembles one compute tile, one GPU tile, and one I/O tile atop a passive base tile using Intel’s Foveros-S advanced packaging. Both compute tile variants use Intel 18A. The Xe3 GPU options are a 4-core GT1 tile on Intel 3 and a larger 12-core GT2 tile on TSMC N3E. Both I/O tile variants use TSMC N6. [1], [2] Our analysis centers on the PTL-U compute tile, both the 4-core and 12-core GPU tiles, as well as the 12-lane I/O tile. In conventional chips, power and signal are routed through the same frontside metal stack towards the device frontend. Power rails consume scarce routing resources near the transistors, while tall via stacks carry VDD and VSS from the coarse upper wires to local rails. Backside power delivery (BSPD) moves the main power network behind the transistor layer, to the backside, separating it from frontside signal routing. We covered BSPD and its impacts in 2024. [3], [4], [5] Intel’s BSPD implementation, branded as “PowerVia”, routes power through dedicated backside metals to nano-TSVs, which connect those rails to local source/drain (S/D) contacts. Implementing that separation requires Intel to build the interconnect stacks from both sides of the wafer. The frontside comprises the M0-M14 signal stack, while the backside comprises the BM0-BM5 power stack. M0 and BM0 are closest to the transistors. The nano-TSVs connect the two sides, but Intel patterns and etches each via from the front after forming the contacts. A narrow via runs from the side of the contact deep into the silicon substrate. Intel then completes the frontside signal metal stack, bonds the wafer to a carrier, flips it and removes the original substrate until the buried via tips are exposed. The backside metal stack is then deposited directly on the revealed vias. The nano-TSV and backside-via profiles taper in opposite directions because Intel forms them from opposite sides of the wafer. The transistor structures form the FEOL. Local contacts and nano-TSVs connect them to the wiring. M0 begins the frontside interconnect stack. The silicon carrier remains attached above the frontside interconnects. It supports the device wafer during substrate removal and backside processing and remains part of the finished chip’s thermal path. PowerVia removes the main power distribution from the congested frontside metals, routing supply through shorter and wider backside wires. Its lateral landing still occupies area in the standard cell, so it recovers less cell area than a direct backside contact. [3] Nano-TSVs beside the logic devices carry VDD or VSS from the backside power network, while signal connections continue upward through the frontside metals. Backside Interconnects Samsung SF2 data is included for comparison to Panther Lake’s within this article. SF2 is the incumbent GAA foundry node but lacks BSPD, serving as a useful reference to evaluate 18A. A full teardown of Samsung’s S26 products, processed on SF2, will be shared soon.Nanosheet-cut EDS comparison. The PowerVia supply path runs from the backside Cu rails through Mo-lined W nano-TSVs to the local transistor contacts. In this cross section, the tapered connection spans roughly 150 nm from the contact level to BM0. The Ta liner confines Cu and promotes adhesion to the surrounding stack; the AlOₓ etch stop controls the next dielectric etch above the rail. Dielectric beneath the ribbons electrically separates the devices from the backside wiring and removes the conducting silicon body below the channel. [6] AlOₓ serves as an etchstop (ES), enabling endpointing and protecting the underlying layers. Low-volatility aluminum fluoride reaction products resist the fluorinated plasma, allowing a thin AlOₓ film to protect the metal while the surrounding low-k dielectric is removed. [6], [7]. While the BM0 and layers above the M1 lines show double AlOx layers, Our SMIC N+3 teardown showed single AlOₓ layers. SMIC uses a simpler local AlOₓ substack, while the remaining cap and etch sequence provide the required landing protection. So why double layers? The closely spaced AlOₓ doublets provide two protected endpoints in the etch sequence. Intel documents an AlOₓ/SiN/AlOₓ stack that explains the benefit. The main dielectric plasma etch stops on the first AlOₓ film; a selective wet clear opens that film; a second plasma etch removes the intermediate SiN and stops on the second AlOₓ film. The final wet clear exposes the metal landing surface. SiN is the intermediate dielectric in Intel’s published example. [8] The second stop protects the metal through a cap breakthrough. Wide openings can etch faster than narrow ones, and etch depth varies across the wafer. Metal under an early-clearing opening would otherwise be exposed while other openings still need more etching. Staged protection widens the process window and reduces metal erosion, corrosion and void formation. [8] TSMC documents AlN/AlOₓ/SiOC/AlOₓ above Cu, with AlN blocking Cu diffusion, and a simpler AlN/SiOC/AlOₓ variant that omits one AlOx film. [9] Levels with different opening sizes, aspect ratios, pattern densities and cap materials need different etch margins. A double AlOx stop is useful where another protected endpoint justifies the added processing. The extra film adds formation, selective opening and cleaning steps, plus another set of interfaces to control adhesion, moisture, and stress. These blanket films are opened through the existing via pattern, so each film does not require another lithography mask. AlOₓ adds parasitic capacitance when it replaces lower-k dielectric; two thin AlOₓ films can nevertheless contain less AlOₓ than one thick film. Total thickness, placement, and theintermediate dielectric determine the electrical cost. Deposition chemistry also changes AlOx permittivity and residual hydroxyl content, which can oxidize the underlying metal. [7], [8], [10], [11] The backside stack separates into relatively fine BM0-BM2 wiring near the devices and coarser BM3-BM5 power distribution. The largest pitch increase occurs between BM2 and BM3. BM0’s pitch closely matches the logic-row height, fitting local power delivery to the cell rows. Higher levels aggregate current through larger conductors: routing density becomes less important than low resistance and current capacity as the network approaches the package. This hierarchy provides wide power wiring for the power delivery network without consuming scarce frontside signal-routing resources. [3] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Frontside Interconnects Intel 18A combines Mo-lined W contacts and nano-TSVs with a separate backside Cu power network. Samsung SF2 keeps power on the frontside, using Ti-based contact interfaces and Ta-based barriers and Co liners around Cu wiring. In 18A standard-cell rows, backside power rails supply the devices through nano-TSVs within the cells, freeing frontside routing resources. Samsung’s M0 accommodates both power and signal connections. From the device toward M0, the connection runs through a Ti-based S/D interface, W contact fill, a Mo-lined W via, and the Cu M0 wire. Mo supplies a conductive nucleation and adhesion layer for W, replacing the resistive TiN liner used in conventional W integration. This increases the effective conduction volume within the feature while retaining W fill and its established polishing, cleaning and etching processes. Intel’s Mo/W patent describes this integration tradeoff. The nano-TSV uses the same Mo-lined W construction in the backside supply path. [12] The move from TiN to Mo is an incremental change. While a full Co or Mo fill can also reduce the volume lost to liners in very small features, it requires new integration schemes that increase complexity and risk. Cu remains attractive for wider wires due to its low resistance. As wires and vias shrink, the diffusion barrier consumes an increasing fraction of their cross-section. [12], [12], [14] Intel uses Co/Ru liners at M0-M1, Co at M2-M4, and Nb at M5-M9. The lower-level liners help Cu adhere and reduce void formation during trench fills. Applied Materials’ Endura has new thermal control that facilitate wetting process, so the thin film continuity is good enough that good capillary pressure will drive Cu atoms to the via bottom without voiding. Intel’s choice to use Nb is particularly interesting. Intel’s Nb patent describes a conductive diffusion barrier intended to reduce the barrier’s contribution to resistance relative to conventional Ta-based barriers, particularly at via bottoms where all current crosses the barrier. The patent pairs Nb in coarser levels with the option of lower-cost PVD processing. [15], [16] The upper metal layers support thicker barriers formed through physical vapor deposition (PVD) despite its worse coverage and uniformity. Meanwhile, the lower metal layers require thinner barriers deposited through conformal atomic layer deposition (ALD). Co/Ru adds another material interface and requires controlled deposition and Cu fill. Changing liners and barriers by metal layer allows Intel to optimize interconnect resistance, process complexity, and reliability. [15, 16] RibbonFET, Intel’s name for its gate-all-around FETs (GAAFETs), replaces the FinFET’s vertical fins with four stacked horizontal silicon nanosheets, allowing the gate to surround the channel on every side. The path to GAAFET begins with the planar transistor. A planar MOSFET places the gate above the channel between its source and drain. Pairing an NMOS with a PMOS transistor creates a CMOS inverter, in which the NMOS pulls the output low for a high input, and the PMOS pulls it high for a low input. The gate must retain electrostatic control of the channel to ensure clean switching. As gate lengths shrank, the drain began to compete with the gate for that control, increasing off-state leakage. Electrostatic control was restored through an architectural evolution that raised the channel into a vertical fin and wrapping the gate around three sides. Called “FinFET”, this new architecture packed more effective channel width into a smaller footprint. Further scaling made it harder to maintain both drive current and leakage within smaller cells, and reintroduced the same problems planar MOSFETs faced. Nanosheet GAAFETs close the fourth side by replacing the vertical fin with a stack of horizontal nanosheets, each surrounded by the gate. The tighter electrostatic control suppresses leakage at shorter gate lengths while stacking adds effective channel width within the cell footprint. In a FinFET process, channel width changes in discrete steps as designers must add or remove whole fins. Nanosheet width can instead be adjusted continuously within the process’s design rules. Wider sheets increase drive current, while narrower sheets reduce capacitance at the cost of drive current. Intel 18A uses stacks of four nanosheets each and varies their widths across logic and SRAM. At the process level, adding more sheets to each stack increases effective channel width and drive current, but complicates fabrication. RibbonFET vs MBCFET Samsung began GAAFET production in 2022 with SF3E, following with SF3 and now SF2. Its ‘MBCFET’ provides a useful structural comparison with Intel’s first RibbonFET implementation. [17] STEEL is digging deeper into SF2, used in the Exynos 2600, and TSMC’s GAAFET N2, used in Apple’s A20 Pro, in upcoming newsletter articles. We’re throwing some teasers on X. Let’s compare Samsung SF2’s MBCFET with Intel 18A’s RibbonFET. Subscribe Even to the untrained eye, Intel’s extra nanosheet is obvious. Intel stacks four ribbons to Samsung’s three. Samsung’s sheets are much wider in these fields, so both sheet count and width matter to the available channel perimeter. Sheet width also changes which silicon surfaces carry current. On conventional (001) silicon, wide nanosheets emphasize the broad top and bottom surfaces, favoring electron transport; the larger sidewall contribution in a narrow sheet favors hole transport. Thinner sheets improve gate control but increase confinement and scattering. This makes width and thickness part of the NMOS/PMOS balance, alongside strain and threshold voltage. [18], [19] GAAFET designs like 18A use different work-function-metal (WFM) stacks for NMOS and PMOS. Around each ribbon, a thin SiOx interfacial layer separates the silicon channel from the HfOx high-k dielectric, with La providing dipole tuning and the WFM wrapping the dielectric. NMOS uses a TiAl-based stack, while PMOS uses TiN WFM. W fills the remaining gate trench, providing a lower-resistivity path where the work-function layers are no longer needed. In this field, the PMOS stacks leave room for W between ribbons, while the NMOS stacks occupy more of those gaps. A silicon-based dielectric marks the P/N boundary, allowing the PMOS and NMOS gates, sharing the same gate trench, to be processed sequentially. Fast logic paths, retention circuits, and SRAM need a family of threshold options. Changing threshold without substantially changing device dimensions, capacitance or fabrication complexity is valuable. FinFET processes typically use different work-function-metal stacks. In a four-ribbon GAA stack, the narrow sheet-to-sheet gap limits how much WFM can fit around each channel. La in the gate dielectric creates interfacial dipoles at the SiOx/HfOx boundary, shifting effective work function and tuning threshold voltage. This gives Intel another control alongside its NMOS and PMOS WFM stacks. Low-threshold devices improve critical-path drive; higher thresholds reduce leakage elsewhere. Dipole tuning is especially useful in GAA because it changes threshold without consuming the narrow intersheet gap with thicker WFM. Precise control of La incorporation, diffusion and interface quality has long been a challenge, limiting viability in high volume production but is now seen from every leading-edge foundry. Intel’s patent describes depositing a dipole-forming oxide above HfOx and annealing it toward the interfacial oxide before completing the work-function and fill metals. This separates threshold tuning from the space available for metal. Newer research addresses the thermal cost: imec’s 2026 dipole-middle research inserts the shifter between two HfOx depositions, shortening the diffusion path while protecting SiOx during patterning. [20], [21]Matched-cut EDS, Intel 18A (left) vs. Samsung SF2 (right). Intel retains raised source/drain epi beneath its contacts, while Samsung recesses W deep into the epi to form a V-shaped Ti-lined interface. The deeper contact increases metal-to-semiconductor area and shortens the current path from the lower sheets, reducing contact and spreading resistance. It also removes epi volume and brings the contact etch closer to the channel ends. Retaining more epi preserves the material available for strain transfer, especially from SiGe into PMOS. These geometries balance contact access against stress engineering and etch margin. [22], [23] Samsung stacks three sheets to Intel’s four ribbons, and both processes use sheet width to tune drive strength. In our Samsung cross-sections, widths range roughly from 19 to 30 nm in the NPU rows and 37 to 50 nm in the CU cell. The Samsung nanosheets taper, with the widest sheet at the bottom and the narrowest at the top. Both processes use HfOx gate dielectric and Ti-based work-function stacks, with Al in the NMOS stack. In the Samsung devices shown here, the dielectric and WFM occupy the intersheet gaps, leaving W above the top sheet. Intel’s PMOS stack leaves more room between ribbons, and W fills those gaps while the thicker NMOS stack leaves W mainly in the upper trench. Gate-stack EDS maps. The W between Intel’s PMOS ribbons provides a conductive path close to the lower gates. Where WFM fills the entire gap, the gate still surrounds the channel, but voltage reaches it through the more resistive work-function films. Thinner WFM and dipole tuning preserve room for low-resistivity fill; Mo and Ru are alternative fill metals being developed for further scaling. [24] A masked, sequential WFM flow explains the different gate heights and inter-nanosheet fill. The proposed sequence below shows how separate NMOS and PMOS work-function steps produce that geometry. Enabled by the BSPDN process, Intel replaces the dense-logic silicon subfin with dielectric, removing the parasitic conduction path below the ribbons and reducing substrate-related capacitance. A retained silicon body as in classical, non-SOI, planar and FinFET designs needs junction and punchthrough-stop engineering to suppress leakage. Dielectric isolation makes that leakage less sensitive to the subfin doping profile but adds removal and fill steps. It also weakens the direct thermal path through silicon, making the contacts, metal stacks and package more important for heat extraction. [24], [26] Fluorine is concentrated around selected Intel device structures in the maps. WF6 is a standard precursor for W nucleation and fill, while barrier films protect adjacent dielectrics from fluorine attack. Low-fluorine W processes reduce the residual-F burden. Chloride-based precursors avoid introducing F during W deposition, but require control of chlorine attack, nucleation and fill quality. The integration target is a continuous, low-resistance W path with a thin protective liner and minimal chemical damage to the surrounding stack. [20], [27], [28] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. We measured cell height, gate pitch, metal geometry, and ribbon dimensions at the XTEM sites shown below. The tables group these dimensions by site and device polarity. Our “sheet cuts” cross the silicon channel and show the ribbons end-on. “gate cuts” run along the channel through successive gates. The 18A logic cell dimensions point to a five-track logic library while the N3E and Intel 3 cell dimensions evidence a seven-track logic library. The DDR-PHY uses wider M0 wires and much larger spacing than core logic. That trades routing density for lower wire resistance and weaker coupling between neighboring nets. The geometry suits the current delivery and coupling requirements of analog, clock, and I/O circuitry. PowerVia lets 18A combine a compact cell height with wider M0 geometry by moving the main power rails off the signal-routing tracks. That relaxes local wire scaling while preserving a small cell footprint. Cell height and gate pitch set the geometric density; pin access and routability determine how much of it a real block can use. [29] The biggest takeaway from our gate-pitch measurements is that Intel 18A compute logic and TSMC N3E GPU logic have similar density in the Bohr representative-cell model. The 18A example is 18.6% denser than the Intel 3 GPU example. Gate pitches are nearly identical across the three sites, so cell height drives most of the difference. The Bohr model combines a four-transistor NAND2 spanning three gate pitches and a 32-transistor scan flip-flop (SFF) spanning nineteen pitches, weighting their densities 60:40. The sensitivity column shows how independently changing cell height and gate pitch by ±1 nm changes the result. This compares representative cell geometries; whole-die density also depends on cell mix and placement. The 18A P-core gives M0 substantially more metal cross section than the N3E vector engine. Treating each profile as a trapezoid gives 2.63 times the area per line and 1.84 times the area after normalization by routing pitch. The larger section reduces the geometric contribution to line resistance and lowers current density for a given current. Taller and wider wires also add capacitance, so circuit delay depends on the balance of resistance and capacitance. The DDR-PHY has less metal area per routing width than the 18A core fields, while remaining above N3E. [30] Area = height × (top CD + bottom CD) / 2, including liners. Area/pitch normalizes by routing width. Taper is the symmetric sidewall angle from vertical, with the largest angle belonging to the DDR-PHY. Compute tile The measurements show how ribbon dimensions and gate-stack geometry vary across the compute tile and between NMOS and PMOS to balance channel drive, gate load and the space needed for the dielectric/WFM stack across logic, SRAM and the DDR-PHY. Width mainly changes available channel perimeter; thickness also changes electrostatic control and carrier confinement. Gate-stack thickness then determines the space left for low-resistivity fill P-core and LP E-core logic Both the P-core and LP E-core use multiple nanosheet widths. Widths are measured on high-magnification XTEMs while wider-field images demonstrate additional width choices within the LP E-core. Multiple widths are expected even within an LP E-core. Timing-critical paths, buffers and cells with different fanout need different drive strengths. The lower-magnification fields show this width diversity beyond the sites quantified in the table. L2 and L3 SRAM GAA gives SRAM designers another way to balance the pull-up (PU), pass-gate (PG), and pull-down (PD) transistors. FinFET bitcells set device strength through fin count while GAA adds nanosheet width as a sizing knob. In a 6T SRAM cell, a strong pull-down relative to the pass-gate limits read disturbance, while a strong pass-gate relative to the pull-up improves writability. During a write, the pass-gate and write driver pull the node storing “1” below the inverter trip point. During a read, the pull-down holds the node storing “0” low. Bias, threshold voltage, mismatch and assist circuitry set the remaining margin. FinFET high-current cells commonly use a PU:PG:PD fin-count pattern of 1:2:2, a device-sizing ratio rather than a current ratio. Ribbon width lets Intel balance SRAM strengths without adding whole fins. The L2 cell uses its narrowest ribbons for PU and widest for PD, improving writability and read stability respectively. Intel’s disclosed HCC operates without assist; its denser HDC uses negative-bitline write assist. Pulling the selected bitline briefly below ground increases pass-gate overdrive so it can overpower the pull-up at lower supply voltage. That buys density and low voltage writability at the cost of boosting circuitry, switching energy, and additional voltage stress that must be controlled. [31], [32] Four rectangular ribbons give the perimeter = 8 × (width + thickness), before corner rounding. PG/PU is 1.49 and PD/PG is 1.16. The L3 structures closely resemble L2 in layout and cell height. Fewer L3 nanosheet widths are tabulated because fewer high-magnification images were available. DDR PHY The DDR-PHY trades density for controlled analog behavior and reliable off-chip signaling. It contains drivers, receivers, delay circuits, and calibration logic that set drive strength, sampling time, and voltage margin. Repeated four-sheet devices with similar widths fit the use of regular transistor units for matching and programmable drive. Its wider local wiring provides room for current delivery and separation of sensitive signals, while consuming more area than a dense core-logic grid. The layout serves the memory channel’s electrical requirements as well as digital logic density. [33] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Intel 3 GPU devices Vector engine logic Intel 3’s XVE logic uses two-fin PMOS and NMOS devices with power rails in M0. Its cell height and M0 pitch give a seven-track geometry, two tracks more than the 18A logic. One-fin groups also appear among the two-fin devices. Intel 3 L2 SRAM The Intel 3 L2 SRAM uses the familiar HCC sizing pattern: one PU fin, two PG fins, and two PD fins. N3E GPU devices Vector engine logic The N3E XVE field contains repeated two-fin devices with seven-track cell geometry. N3E remains a FinFET process, giving Panther Lake a direct FinFET-to-RibbonFET comparison. N3E L2 SRAM The N3E L2 SRAM uses the same PU:PG:PD fin-count pattern of 1:2:2. Panther Lake-U follows Lunar Lake’s floorplan quite closely. Both pair 4 P-cores with 4 LP E-cores and NPU, media and display engines in similar locations. Lunar Lake also uses Xe2, the direct predecessor to Panther Lake’s Xe3 GPU. This makes Lunar Lake the most direct basis for our comparisons. Arrow Lake differs in core count and uses the older Xe-LPG GPU architecture, so we only use it where it offers a more direct component-level comparison. Compute tile Panther Lake compute-tile floorplans remain sparse even months after launch. Intel 18A’s backside metal and dielectric stack must be removed without damaging the underlying structures before a clean transistor-level floorplan can be imaged. Most published die shots hide or heavily process the background, but we are quite proud of the die shot we achieved and are excited to show the work we have done. We measured the areas of the key components on the compute tile and compared them with their Lunar Lake predecessors on TSMC N3B. These help us to capture changes in block area and compare the two chips across process nodes and designs. Our total tile areas exclude the scribe-line area. The compute-plus-GPU subtotal below uses the PTL-U compute tile and GT1 GPU; it excludes the I/O tile and passive base. Individual block areas use the boundaries marked on the floorplans The compute-plus-GPU row is recomputed from the displayed PTL-U and GT1 areas. Component rows use their stated per-region counts and are not an additive partition of the whole tile. The P-core area remains almost unchanged between Lunar Lake and Panther Lake, despite L2 capacity increasing from 2.5 MiB to 3 MiB. Arrow Lake uses the same Lion Cove core as Lunar Lake but also has a 3 MiB L2. Cougar Cove fits 20% more L2 into the same P-core area. The larger private cache keeps more of each core’s working set close to its execution units, reducing access to shared L3 and DRAM. Extra capacity adds storage leakage and lookup energy, so designers balance it against avoided lower-level accesses. The shared P-core L3 cache also shrank by 14.8%. [2] Cougar Cove combines a similar footprint with Intel’s reported power-efficiency improvements. RibbonFET’s tighter channel control reduces leakage, while PowerVia reduces supply droop and allows tighter voltage guardbands. [1] Darkmont’s four-core LP E-core cluster is 5.0% smaller than Skymont’s on Lunar Lake, with most of the reduction in its L2 regions. The 1 MiB region shrank by 8.4% and the 1.5 MiB region by 14.9%. The tag arrays also use one fewer visible row. Tags identify which memory addresses the data array holds, so rearranging them changes the cache’s layout and wiring without requiring less data capacity. [2] The LP E-cores share one L2. This pools capacity and avoids duplicating all the cache machinery, but the four cores contend for its banks and bandwidth. Their separate cluster also keeps light work away from the performance cluster and its L3, allowing that larger domain to sleep. [1], [2] Cache area includes more than the storage cells. Tags identify each line, decoders select rows, sense amplifiers read the small bitline signal, and wires connect to the banks. Splitting an array into smaller sections shortens wordlines and bitlines, improving access speed, but duplicates peripheral circuits. Panther Lake’s smaller cache regions therefore reflect the complete memory implementation, including how much of each region is devoted to storage. [34] Unlike Meteor Lake and Arrow Lake, Panther Lake has no separate SoC tile. The NPU, LP E-cores, memory controllers, PHYs, media and display engines now share the compute tile. This removes an active die and keeps CPU memory traffic on one die. The cost is moving PHY and I/O-related circuitry onto 18A: drivers, receivers and analog circuits must still meet external voltage, loading and signal-integrity requirements, so their area does not shrink like dense digital logic. [1], [2] The biggest shrink comes from the NPU, which occupies 36.9% less area. NPU 5 consolidates the same total INT8 MAC count into half as many neural compute engines. Each of the three NCEs has a larger MAC array to make the complete NCE envelope 22.6% larger than an NPU 4 engine. Consolidation also halves the number of scratchpads and SHAVE DSPs, from 12 to 6. The MAC array handles matrix multiplication and convolution, while SHAVE executes vector and custom operations that fit the array poorly. [1], [2], [35] The paired floorplans identify each NCE envelope and its scratchpad, MAC, and SHAVE regions. Each measured MAC polygon is counted once per NCE in the area accounting below. The scratchpads store weights, activations, and intermediate results near the MAC arrays, allowing repeated use without fetching them again from DRAM. Halving their number delivers the largest measured area saving but leaves less local storage for the same total MAC count. Layers that no longer fit locally require smaller working tiles or more transfers of intermediate data. The benefit depends on keeping the enlarged arrays busy while managing that tighter storage budget. [36] NPU 5 also adds native FP8. Using half the operand width of FP16 reduces storage and transfer demand, helping workloads fit the smaller local memory budget. Lower precision and format-dependent range make scaling and model validation part of deployment. Hardware activation functions further reduce work that would otherwise occupy the programmable DSPs. [1], [2] Microsoft requires an NPU to deliver at least 40 TOPS for Copilot+ PCs. Both Lunar Lake and Panther Lake meet this threshold, but Panther Lake uses significantly less silicon. GPU tiles Panther Lake is Intel’s first product with Xe3, its latest GPU architecture. It offers two different GPU tiles: a smaller GT1 tile with 4 Xe3 cores on Intel 3 and a larger GT2 tile with 12 Xe3 cores on TSMC N3E. Panther Lake allows us to compare the same GPU architecture across both Intel 3 and TSMC N3E. Wildcat Lake adds a third Xe3 implementation on Intel 18A. A future newsletter will detail Xe3 and its implementation differences across all three process nodes. GT2 scales Xe3 to a different physical layout, with render slices arranged vertically instead of GT1’s horizontal arrangement. Slice placement sets the distances to shared cache banks and the D2D interface. Those wires consume area and add delay, so scaling the number of Xe cores also requires a new balance of cache placement, routing and timing. [1] What’s immediately obvious is that the GT2 tile on TSMC N3E has much smaller Xe cores than GT1. These block areas include logic, caches, and routing. An Xe core on the GT1 tile is ~69% larger than one on Lunar Lake, and ~55% larger than one on GT2. Intel 3 therefore uses substantially more area per Xe core. The block-area gap exceeds the measured logic and SRAM density gaps, bringing routing, timing targets, cell mix, and floorplan allocation into the comparison. The measured vector/matrix engine region is almost unchanged between Lunar Lake and Panther Lake’s GT2 tile. Xe3 retains eight 512-bit vector engines and eight 2048-bit XMX engines per core. Its gains also come from feeding those engines more effectively: more resident threads hide stalls, and variable register allocation lets shaders trade registers per thread against the number of threads kept active. [1] The shared L1/SLM capacity increased by 33% from 192 KiB to 256 KiB, while its area increased only 5%, raising effective density by 27%. L1 retains reused cache lines, while software-managed SLM lets a thread group share data locally. Both reduce traffic to more distant memory. Allocating more SLM per group can also limit how many groups reside on a core at once. [1], [37] The GT1 tile carries 4 MiB of L2 against 16 MiB on the GT2 tile. GT1 divides its L2 cache into four 1 MiB banks, while GT2 uses eight 2 MiB banks. Each bank contains 128 macros, but each N3E macro stores 16 KiB, twice the Intel 3 macro’s 8 KiB capacity. The N3E macro is only 54% larger while holding twice as many bits, giving it 30% higher density: ~23.7 Mbit/mm² versus 18.3 Mbit/mm². Including bank-level circuitry, the gap widens to ~16.9 Mbit/mm² on GT2 versus ~10.4 Mbit/mm² on GT1. GT2 gains density with its macros storing more bits per unit area, and those macros occupy more of each cache bank. Larger macros spread decoder and sense-amplifier overhead across more storage, while a more compact bank layout reduces the share spent on control and routing. The compromise is longer wordlines and bitlines that carry more capacitance. [34] I/O tile Panther Lake uses two I/O tile variants, both fabricated on TSMC N6. The smaller one provides 4 PCIe 5.0 and 8 PCIe 4.0 lanes and serves lower-tier systems as well as those without a discrete GPU, while the larger one adds 8 PCIe 5.0 lanes, bringing the total to 20 lanes, for discrete-GPU connectivity. Panther Lake SKUs with the larger 10- or 12-Xe GPUs use the smaller I/O tile. [38] The smaller I/O tile adds a PCIe 4.0 block and a Thunderbolt block to Lunar Lake’s I/O layout, providing four additional PCIe 4.0 lanes and another Thunderbolt 4 port. Its repeated N6 blocks retain nearly identical areas and layouts. Reusing these proven PHYs and controllers avoids porting and requalifying external interfaces on 18A, where faster digital logic offers less benefit to circuits constrained by the off-chip link. [38] SemiAnalysis’s teardown lab (STEEL) dives deep into the world’s advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. We’re hiring technical experts from system to transistor and everywhere in between. Check out our Careers page. Panther Lake offers scalability and modularity through its disaggregated packaging that partition compute, GPU, and I/O silicon into separate tiles allowing for a suite of tile configurations. This partitioning makes the package part of Intel’s node economics as it determines how much leading-edge wafer area each product consumes, which functions can remain on other processes, and how much configuration freedom Intel can offer from a shared set of tiles. Furthermore, fabricating the compute and GPU tiles separately confines the new 18A process to the compute tile and allows graphics and I/O to use other, more established, and more cost-effective processes. For Panther Lake, the GPU and I/O tiles are assembled alongside the compute tile on a passive silicon base using Foveros-S. Intel’s current technology brief lists a nominal 36 µm pitch for Foveros-S. Through-silicon vias (TSVs) in the base connect the fine wiring above to the larger package connections below. The functional tiles sit side by side on that passive base in a 2.5D configuration. [39] Our cross-section through the compute and GPU tiles shows the package’s wiring hierarchy. Microbumps connect each active tile to the passive silicon base; its fine redistribution layer (RDL) carries the short, dense tile-to-tile links. TSVs carry connections through the base to the package substrate, which fans them out to the much coarser motherboard solder joints. The base supplies interconnect, while computation remains in the active tiles above it. [39] At the compute-tile edge, the higher-magnification inset shows a local microbump spacing of approximately 25.24 µm and a feature width of 12.33 µm. These local spacings are finer than Intel’s nominal Foveros-S value. The X-ray fields further confirm tighter neighboring bumps, consistent across every die-to-die area found on each tile. Additional X-ray analysis is offered after the paywall. Putting the memory controller beside the CPU removes the D2D transfer that CPU memory requests required in Meteor Lake and Arrow Lake. This avoids the extra transmitter, receiver, and link traversal, saving interface energy and latency. Panther Lake’s separate GPU still crosses a D2D link to reach DRAM, so its larger local caches also help contain package traffic. [1], [40] Smaller dies are less likely to contain a random fatal defect, and screening them before assembly prevents one bad tile from consuming a complete package of good silicon. Reuse also spreads design and qualification work across more products. Against those gains, Intel pays for the passive base, D2D circuits, extra bonding and test steps, and losses during assembly. Cost per working product across the portfolio captures the combined effect of wafer yield, reuse, test, and assembly. [29] Wildcat Lake packaging Intel launched Core Series 3, formerly Wildcat Lake, on 16 April 2026 for value mobile and edge systems. Wildcat Lake keeps 18A but removes the passive base and combines more functions on one die to simplify the package. The two products therefore reveal two distinct ways to commercialize the same leading-edge process. [41] Wildcat Lake’s 18A die combines up to two Cougar Cove P-cores, four Darkmont LP E-cores, two Xe3 cores and a smaller NPU. A separate platform-controller die supplies I/O, connected through UCIe, Intel’s first processor implementation of the standard. Consolidating graphics remove a tile boundary and the passive base, reducing assembly complexity for a modest-bandwidth value product. It also ties CPU and graphics scaling to the same die, giving up Panther Lake’s ability to swap in a much larger GPU. [42], [43] In July 2021, Intel CEO Pat Gelsinger set out an ambitious process roadmap aimed at regaining performance leadership by 2025, later described as five nodes in four years. Five years and one CEO later, Intel’s comeback story is not as unambiguously positive as Pat may have hoped. [44], [45] Intel once set the pace for process technology, bringing high-k metal gate technology and FinFETs into volume production years ahead of the rest of the industry. Its 22 nm FinFET process reached consumers with Ivy Bridge in 2012. [46] Intel’s integrated device manufacturing (IDM) model allowed its architects and process engineers to co-optimize products and processes. Starting with Sandy Bridge, Intel dominated x86, while AMD struggled with Bulldozer. That lead faltered at 14 nm and broke at 10 nm. Intel targeted a massive 2.7× density increase, but the node arrived years late and required several revisions before it could support Intel’s full lineup. This delay forced Intel to stretch 14 nm across six generations, while TSMC moved ahead in process technology and AMD recovered in x86. By 2019, Intel was still shipping 14 nm across most of its product stack, with its 10 nm client ramp focused on Ice Lake mobile processors. Meanwhile, TSMC was shipping N7 and N7+, and AMD’s Zen 2 compute chiplets used N7 to raise core counts and improve efficiency. Intel’s process failures were central to its decline, but unsound business decisions furthered their downward slide. Product delays compounded product mistakes, pushing client, server, and FPGA roadmaps off schedule. Several attempts to enter AI (Nervana and Gaudi) and networking (Tofino) also failed to establish lasting businesses. Intel’s recovery has focused on consumer CPUs and advanced packaging. Tiger Lake, Alder Lake, Lunar Lake and now Panther Lake have restored Intel’s consumer roadmap. On the process side, Intel 4 shipped with Meteor Lake, Intel 3 with Granite Rapids and Sierra Forest, and Intel 18A with Panther Lake. Intel has also made advanced packaging part of its foundry offering. However, Intel is still playing catch-up in servers. Several Xeon generations arrived years late and trailed contemporary AMD and Arm server CPUs in performance, efficiency, and core count. The process roadmap is back, but Intel does not hold the same process-technology leadership position it held prior to 10 nm. The introduction of gate-all-around nanosheets and backside power delivery are two of the biggest changes to transistor integration in a decade. Intel took on both changes at once: 18A paired its first RibbonFET with PowerVia in Panther Lake. Panther Lake is a substantial manufacturing milestone. Our cross-sections show how RibbonFET and PowerVia reshape local contacts and wiring, while the floorplans show where architectural consolidation and process choices save area. A sustained competitive lead depends on product performance, cost, yield, and the next implementation. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page.. 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Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
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