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Cognition is the first customer running @NVIDIA Vera Rubin, powered by CoreWeave! Hopper in 2022. Blackwell in 2024. Now Vera Rubin: On SWE-2 inference, the new chips deliver about 4.8x more token throughput than GB200 at the same decode speed. More compute, better agents!

Cognition

187,417 subscribers

118,479 görüntüleme • 3 gün önce •via X (Twitter)

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Jared Zoneraich profil fotoğrafı

Jared Zoneraich3 gün önce

@nvidia @CoreWeave Hardware also matters!

Felix Schlegel profil fotoğrafı

Felix Schlegel3 gün önce

@nvidia @CoreWeave more compute, better agents!

Chris W profil fotoğrafı

Chris W3 gün önce

@nvidia @CoreWeave I'd say thanks for taking care of getting SWE-2 on this amazing hardware!

Matt Bergland profil fotoğrafı

Matt Bergland3 gün önce

@nvidia @CoreWeave lfg

Kartik profil fotoğrafı

Kartik3 gün önce

@nvidia @CoreWeave So that's why the speeds got faster today!

Jay Grant profil fotoğrafı

Jay Grant3 gün önce

@nvidia @CoreWeave monumental

ANUP profil fotoğrafı

ANUP3 gün önce

@nvidia @CoreWeave cognition is not going to slow down any sooner 🔥

Jake Cosme profil fotoğrafı

Jake Cosme3 gün önce

@nvidia @CoreWeave Always stay shipping!

Mitchell Mecum profil fotoğrafı

Mitchell Mecum3 gün önce

@nvidia @CoreWeave Accelerate!!!

Mark Vassilevskiy profil fotoğrafı

Mark Vassilevskiy3 gün önce

@nvidia @CoreWeave 🔥🔥🔥

cashd profil fotoğrafı

cashd3 gün önce

@dabit3 @nvidia @CoreWeave Love it! But music is too loud over his speech

Justin profil fotoğrafı

Justin3 gün önce

@sandeepDshah @nvidia @CoreWeave ⚡️

Alex Volkov profil fotoğrafı

Alex Volkov3 gün önce

@nvidia @CoreWeave LFG!

J A Z I I profil fotoğrafı

J A Z I I3 gün önce

@nvidia @CoreWeave now that's banger

Anderson profil fotoğrafı

Anderson3 gün önce

@nvidia @CoreWeave 4.8x the tokens per second so the agent can now be wrong at a much higher speed

Mark Murphy profil fotoğrafı

Mark Murphy3 gün önce

@nvidia @CoreWeave Congrats! Been using Devin daily. Keep up the awesome work!

Ron profil fotoğrafı

Ron3 gün önce

@nvidia @CoreWeave @KampnerSam

y profil fotoğrafı

y3 gün önce

compute always wins

Lorenzo Porras profil fotoğrafı

Lorenzo Porras3 gün önce

@nvidia @CoreWeave

Saiyam Pathak profil fotoğrafı

Saiyam Pathak3 gün önce

@dabit3 @nvidia @CoreWeave crazy!!

Diana Zawadzki profil fotoğrafı

Diana Zawadzki3 gün önce

@nvidia @CoreWeave So epic!

diedbroke profil fotoğrafı

diedbroke3 gün önce

@nvidia @CoreWeave I bet you factory already running quantum computers. That's why y'all behind.

bnistordev profil fotoğrafı

bnistordev3 gün önce

@nvidia @CoreWeave I really love when I see Cognition name under this kind of announcements.

Aman profil fotoğrafı

Aman3 gün önce

@nvidia @CoreWeave this is gonna be an insane combo for agentic workloads

Dan Shamir profil fotoğrafı

Dan Shamir3 gün önce

@nvidia @CoreWeave You also steal board members from competitors. Losers

Aleksandr Grishin profil fotoğrafı

Aleksandr Grishin3 gün önce

@nvidia @CoreWeave 🥳🥳

高嗯嗯 profil fotoğrafı

高嗯嗯2 gün önce

@nvidia @CoreWeave swe 如果一直免费我将一直订阅

The SI Therapist profil fotoğrafı

The SI Therapist3 gün önce

@nvidia @CoreWeave @NVIDIA Vera Rubin delivers 4.8x more tokens on SWE-2 than previous chips. It looks like Cognition and CoreWeave have built something fast for AI coding tasks.

Ibesh profil fotoğrafı

Ibesh3 gün önce

@nvidia @CoreWeave Will the 4.8x throughput gain reduce queue times for Devin users during peak hours?

sophs j. profil fotoğrafı

sophs j.3 gün önce

@nvidia @CoreWeave Love this take

Crio Songo profil fotoğrafı

Crio Songo3 gün önce

@nvidia @CoreWeave 4.8x throughput boost is really impressive. This iteration will definitely push agent performance to a new level.

Gabriel Abi profil fotoğrafı

Gabriel Abi3 gün önce

@nvidia @CoreWeave 4.8x on SWE-2 with same decode speed — that's the unlock for agentic workloads. inference bottlenecks become a thing of the past at this rate

Damian Z. 💛🇪🇺 profil fotoğrafı

Damian Z. 💛🇪🇺2 gün önce

@nvidia @CoreWeave LFG

MOSSE. profil fotoğrafı

MOSSE.3 gün önce

@nvidia @CoreWeave So Jump Trading lied ?

Almost Tomorrow profil fotoğrafı

Almost Tomorrow3 gün önce

@nvidia @CoreWeave How much of that throughput gain translates into a lower cost per completed task, once retries and tool calls are included?

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Nvidia $NVDA CEO just said that Vera Rubin is now in full production The supply chain Nvidia created for Vera Rubin is twice as large as Grace Blackwell

Nvidia $NVDA CEO just said that Vera Rubin is now in full production The supply chain Nvidia created for Vera Rubin is twice as large as Grace Blackwell

Evan

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Jensen Huang said Grok 5 will be 7 Trillion parameter model. On time to train, with the training window fixed at 1 month, the new Vera-Rubin GPU system of Nvidia needs 1/4 the number of systems compared with Blackwell to train the same frontier model. “factory throughput” improves by about 10x over Blackwell, and Blackwell itself was about 10x over Hopper. i.e. overall Rubin is roughly 100x Hopper in factory throughput per watt, which matters hugely, because a 1 GW, $50B data center is power-limited and revenue scales with throughput per watt. --- From Nvidia YT channel

Jensen Huang said Grok 5 will be 7 Trillion parameter model. On time to train, with the training window fixed at 1 month, the new Vera-Rubin GPU system of Nvidia needs 1/4 the number of systems compared with Blackwell to train the same frontier model. “factory throughput” improves by about 10x over Blackwell, and Blackwell itself was about 10x over Hopper. i.e. overall Rubin is roughly 100x Hopper in factory throughput per watt, which matters hugely, because a 1 GW, $50B data center is power-limited and revenue scales with throughput per watt. --- From Nvidia YT channel

Rohan Paul

165,770 görüntüleme • 8 ay önce

Nvidia just revealed Vera Rubin. Ships H2 2026. The numbers are wild: → 10x more performance per watt vs Blackwell → 10x cheaper inference token cost → 4x fewer GPUs to train the same MoE model Energy was the biggest bottleneck in AI. Nvidia just made it 10x cheaper.

Nvidia just revealed Vera Rubin. Ships H2 2026. The numbers are wild: → 10x more performance per watt vs Blackwell → 10x cheaper inference token cost → 4x fewer GPUs to train the same MoE model Energy was the biggest bottleneck in AI. Nvidia just made it 10x cheaper.

Min Choi

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NVIDIA Vera Rubin is in full production and arrives just in time for the next frontier of AI. The #NVIDIARubin platform uses extreme co-design across six new chips to accelerate agentic AI, advanced reasoning and massive-scale MoE model inference. NVIDIA Vera Rubin NVL72: Six new chips, one AI supercomputer — see how we built it.

NVIDIA Vera Rubin is in full production and arrives just in time for the next frontier of AI. The #NVIDIARubin platform uses extreme co-design across six new chips to accelerate agentic AI, advanced reasoning and massive-scale MoE model inference. NVIDIA Vera Rubin NVL72: Six new chips, one AI supercomputer — see how we built it.

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The NVIDIA Vera Rubin platform is a multi-rack pod-scale system, built to process agentic AI and is now in full production. Built through extreme co-design, Vera Rubin unifies five connected rack-scale systems — the NVIDIA Vera Rubin NVL72, Vera CPU rack, Groq 3 LPX, Vera BlueField-4 STX, and Spectrum-6 SPX Ethernet — all purpose-built for global-scale agentic AI infrastructure. Vera Rubin delivers intelligence at scale, with the performance, efficiency and security needed to power the next industrial revolution. Congratulations to Microsoft, Dell Technologies, and CoreWeave for each standing up their Vera Rubin NVL72 engineering racks. Learn more:

The NVIDIA Vera Rubin platform is a multi-rack pod-scale system, built to process agentic AI and is now in full production. Built through extreme co-design, Vera Rubin unifies five connected rack-scale systems — the NVIDIA Vera Rubin NVL72, Vera CPU rack, Groq 3 LPX, Vera BlueField-4 STX, and Spectrum-6 SPX Ethernet — all purpose-built for global-scale agentic AI infrastructure. Vera Rubin delivers intelligence at scale, with the performance, efficiency and security needed to power the next industrial revolution. Congratulations to Microsoft, Dell Technologies, and CoreWeave for each standing up their Vera Rubin NVL72 engineering racks. Learn more:

NVIDIA

49,740 görüntüleme • 4 ay önce

The first-ever measured silicon numbers for NVIDIA Vera Rubin NVL72 showed 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware. The full methodology, why matched interactivity is the honest way to compare a reasoning model, and more:

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📣 CoreWeave and NVIDIA are accelerating the build out of AI factories—token generators that directly drive revenue. This includes adoption of and support for: ✅ NVIDIA Vera Rubin deployment, starting in 2H 2026 ✅ NVIDIA Vera CPU and BlueField-4 STX ✅ NVIDIA Dynamo for inference and NVIDIA Agent Toolkit and OpenShell for long-running agents ✅ NVIDIA DSX Air for digital twins of AI factories Learn more ➡️

📣 CoreWeave and NVIDIA are accelerating the build out of AI factories—token generators that directly drive revenue. This includes adoption of and support for: ✅ NVIDIA Vera Rubin deployment, starting in 2H 2026 ✅ NVIDIA Vera CPU and BlueField-4 STX ✅ NVIDIA Dynamo for inference and NVIDIA Agent Toolkit and OpenShell for long-running agents ✅ NVIDIA DSX Air for digital twins of AI factories Learn more ➡️

NVIDIA AI Infrastructure

10,213 görüntüleme • 5 ay önce

NVIDIA Vera Rubin NVL72 production racks are here. The compute tray is engineered for fast compute, assembly, and serviceability. Manufacturing is 100% automated, and every tray goes together in one minute. Congratulations to Microsoft on the first operational Vera Rubin NVL72 racks, now rolling off Hon Hai Technology Group (Foxconn) Ingrasys lines.

NVIDIA Vera Rubin NVL72 production racks are here. The compute tray is engineered for fast compute, assembly, and serviceability. Manufacturing is 100% automated, and every tray goes together in one minute. Congratulations to Microsoft on the first operational Vera Rubin NVL72 racks, now rolling off Hon Hai Technology Group (Foxconn) Ingrasys lines.

NVIDIA

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The NVIDIA Vera Rubin NVL72 scale-up fabric, built on the sixth-generation NVIDIA NVLink. The NVLink 6 Switch trays connect 72 Rubin GPUs in an all-to-all configuration. The NVLink spine—over 5,000 copper cables make up the vertical NVLink traverse. It securely moves more data than the entire bandwidth of the internet. The single-wide NVIDIA MGX rack design unlocks a cable-free, horizontal NVLink scale-up traverse, running directly on PCB for resiliency at scale. This is how NVIDIA Vera Rubin NVL72 works as one, designed to deliver the lowest token cost and 10x more performance per watt than the previous generation. #NVIDIAVeraRubin

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Vera Rubin is in full production. We just kicked off the next generation of AI infrastructure with the NVIDIA Rubin platform, bringing together six new chips to deliver one AI supercomputer built for AI at scale. Here are the top 5 things to know 🧵

Vera Rubin is in full production. We just kicked off the next generation of AI infrastructure with the NVIDIA Rubin platform, bringing together six new chips to deliver one AI supercomputer built for AI at scale. Here are the top 5 things to know 🧵

NVIDIA

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NVIDIA Vera is heading to Amazon Web Services. NVIDIA’s Ian Buck hand-delivered AWS’s first Vera CPU Server and Vera Rubin GPU to Willem Visser and Supreeth Sheshadri at the AWS HQ in Seattle. Vera is purpose-built for agentic AI: more tokens per dollar, faster results for users, and the compute foundation AI factories need to scale.

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Watch Nvidia CEO Jensen Huang reveal what he described as the state of the art in AI hardware: the new Rubin computing architecture. “Vera Rubin is designed to address this fundamental challenge that we have: The amount of computation necessary for AI is skyrocketing.” Huang said. “Today, I can tell you that Vera Rubin is in full production.” According to Nvidia’s tests, Rubin architecture operates three and a half times faster than the previous Blackwell architecture on model-training tasks and five times faster on inference tasks, and that's just the start.

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$NVDA says it has shipped its first Vera Rubin samples to customers and remains on track for production shipments in 2H. $AMD Helios vs. Vera Rubin is shaping up to be the compute Super Bowl of 2026.

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From the show floor to the AI factory: Hot Chips 2026 was all about extreme co-design to accelerate agentic workloads — the most complex workload in history. Vera CPU, Vera Rubin, Groq 3 LPX, Spectrum-X Multiplane, BlueField-4 Scale-In networking. One full AI stack platform built for agents.

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🚨HUGE: Nvidia is charging MORE for its chips, and Jensen Huang says he did it on purpose. The Nvidia CEO says the company chose to "rip the band-aid off" after memory costs exploded. A single Vera Rubin rack could now cost around $8 MILLION.

🚨HUGE: Nvidia is charging MORE for its chips, and Jensen Huang says he did it on purpose. The Nvidia CEO says the company chose to "rip the band-aid off" after memory costs exploded. A single Vera Rubin rack could now cost around $8 MILLION.

Coin Bureau

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Sachin Katti says OpenAI had Astra optimize its own inference on NVIDIA's Rubin chip, adding another 2x in 72 hours "It's a testament to NVIDIA's hardware that out of the box we got a 3x improvement in throughput. We literally took the same code that we had optimized for Blackwell, ran it on Rubin, got 3x improvement." "Then, can we actually make Astra run agents using Astra as the base model, go optimize this inference of Astra itself on Rubin? It's a recursive loop. The model is figuring out how to optimize its own inference serving on Rubin chips, and over 72 hours the model produced another 2x improvement on the throughput." "Things that would take weeks, if not months, to optimize in the past, we now are getting models that are very capable of actually producing over a weekend." _______ Link and more from Sachin Katti's conversation:

Sachin Katti says OpenAI had Astra optimize its own inference on NVIDIA's Rubin chip, adding another 2x in 72 hours "It's a testament to NVIDIA's hardware that out of the box we got a 3x improvement in throughput. We literally took the same code that we had optimized for Blackwell, ran it on Rubin, got 3x improvement." "Then, can we actually make Astra run agents using Astra as the base model, go optimize this inference of Astra itself on Rubin? It's a recursive loop. The model is figuring out how to optimize its own inference serving on Rubin chips, and over 72 hours the model produced another 2x improvement on the throughput." "Things that would take weeks, if not months, to optimize in the past, we now are getting models that are very capable of actually producing over a weekend." _______ Link and more from Sachin Katti's conversation:

Fireside Alpha

40,013 görüntüleme • 16 gün önce