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NVIDIA paid $20B for Groq. AWS partnered with Cerebras for the same purpose. A quick breakdown of why disaggregated inference is the next thing in AI infrastructure.

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Cerebras

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384,073 просмотров • 3 месяцев назад •via X (Twitter)

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Class 2 of MS&E 435 - Economics of AI Inference - is live! The Groq story alone was worth the class. Why did Nvidia paid $20B for Groq? TLDR: It wasn't about building a better GPU. Groq's deterministic, SRAM-heavy chip disaggregated the decode layer. Same power footprint, 2.5x more tokens. Big thanks to Brad Gerstner and sunny madra for doing this with our class.
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Class 2 of MS&E 435 - Economics of AI Inference - is live! The Groq story alone was worth the class. Why did Nvidia paid $20B for Groq? TLDR: It wasn't about building a better GPU. Groq's deterministic, SRAM-heavy chip disaggregated the decode layer. Same power footprint, 2.5x more tokens. Big thanks to Brad Gerstner and sunny madra for doing this with our class.

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21,841 просмотров • 5 месяцев назад

🚨 Big news! Cerebras is launching six new AI data centers across North America & Europe. This expands our capacity to 40M+ tokens/sec, making Cerebras the first hyperscale cloud for high-speed AI inference. Read more:
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🚨 Big news! Cerebras is launching six new AI data centers across North America & Europe. This expands our capacity to 40M+ tokens/sec, making Cerebras the first hyperscale cloud for high-speed AI inference. Read more:

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27,477 просмотров • 1 год назад

Special thanks to @TareqAmin01 for making the announcement about the further expansion of AI Inference Infrastructure in the Kingdom with Groq during LEAP
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Special thanks to @TareqAmin01 for making the announcement about the further expansion of AI Inference Infrastructure in the Kingdom with Groq during LEAP

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19,394 просмотров • 1 год назад

This is why Nvidia bought Groq. If Groq deploys a ton of low-cost inference chips, demand for training will increase massively. The more inference you have, the more training you need, and vice versa. Nvidia can keep its high margins selling chips for training forever.
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This is why Nvidia bought Groq. If Groq deploys a ton of low-cost inference chips, demand for training will increase massively. The more inference you have, the more training you need, and vice versa. Nvidia can keep its high margins selling chips for training forever.

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"You could imagine yourself actually being 10x more productive." Nolan Dey from the Cerebras Core ML team speaks with Alycia Cary on why speed contributes to intelligence. In agentic workloads like Claude Code, queries can run for hours. Faster inference means more test time compute in the same budget.
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"You could imagine yourself actually being 10x more productive." Nolan Dey from the Cerebras Core ML team speaks with Alycia Cary on why speed contributes to intelligence. In agentic workloads like Claude Code, queries can run for hours. Faster inference means more test time compute in the same budget.

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132,844 просмотров • 1 месяц назад

📣 ANNOUNCEMENT DAY AT CEREBRAS 📣 Today, we are thrilled to share some of the biggest announcements in our company’s history. 📢 Cerebras announces CS-3, the world’s fastest AI Chip with a whopping 4 trillion transistors 📢 Cerebras selects Qualcomm to deliver unprecedented performance in AI Inference 📢 Cerebras and G42 break ground on Condor Galaxy 3, an 8 exaFLOPs AI Supercomputer Read all about it! 📰 CS-3 Press Release: 📰 Cerebras + Qualcomm Press Release: 📰 Condor Galaxy 3 Press Release: #AI #Supercomputer #ExaFLOPs #ML #Training #Inference
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📣 ANNOUNCEMENT DAY AT CEREBRAS 📣 Today, we are thrilled to share some of the biggest announcements in our company’s history. 📢 Cerebras announces CS-3, the world’s fastest AI Chip with a whopping 4 trillion transistors 📢 Cerebras selects Qualcomm to deliver unprecedented performance in AI Inference 📢 Cerebras and G42 break ground on Condor Galaxy 3, an 8 exaFLOPs AI Supercomputer Read all about it! 📰 CS-3 Press Release: 📰 Cerebras + Qualcomm Press Release: 📰 Condor Galaxy 3 Press Release: #AI #Supercomputer #ExaFLOPs #ML #Training #Inference

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128,669 просмотров • 2 лет назад

Introducing the Cerebras Ambassador Program 🌏 We're looking for AI community builders to build your local ecosystem around the world's fastest inference. In the last few months, our community has hosted Cafe Compute Meetups in Berlin, Mexico City, Mumbai, SF, Seattle, and NYC. We want your city to be next! Application link in comments.
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Introducing the Cerebras Ambassador Program 🌏 We're looking for AI community builders to build your local ecosystem around the world's fastest inference. In the last few months, our community has hosted Cafe Compute Meetups in Berlin, Mexico City, Mumbai, SF, Seattle, and NYC. We want your city to be next! Application link in comments.

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102,053 просмотров • 2 месяцев назад

Introducing ⚡️Cerebras MCP Server ⚡️ You can now turbocharge any AI editor that uses MCP for tool calling with 20x faster inference. Here is Claude Code writing files at breakneck speed via Cerebras. Get started now 👇
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Introducing ⚡️Cerebras MCP Server ⚡️ You can now turbocharge any AI editor that uses MCP for tool calling with 20x faster inference. Here is Claude Code writing files at breakneck speed via Cerebras. Get started now 👇

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Running GPT-5.6 Sol Ultrafast on Cerebras, Matthew Berman saw his workflow flip: fewer parallel agents, same productivity, lower mental load. When tokens stop being the bottleneck, the rest of the stack becomes the next layer to optimize. Faster inference opens that door.
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Running GPT-5.6 Sol Ultrafast on Cerebras, Matthew Berman saw his workflow flip: fewer parallel agents, same productivity, lower mental load. When tokens stop being the bottleneck, the rest of the stack becomes the next layer to optimize. Faster inference opens that door.

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46,090 просмотров • 11 дней назад

Introducing Cerebras Inference ‣ Llama3.1-70B at 450 tokens/s – 20x faster than GPUs ‣ 60c per M tokens – a fifth the price of hyperscalers ‣ Full 16-bit precision for full model accuracy ‣ Generous rate limits for devs Try now:
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Introducing Cerebras Inference ‣ Llama3.1-70B at 450 tokens/s – 20x faster than GPUs ‣ 60c per M tokens – a fifth the price of hyperscalers ‣ Full 16-bit precision for full model accuracy ‣ Generous rate limits for devs Try now:

Cerebras

707,967 просмотров • 2 лет назад

Introducing SuperNinja – the world’s fastest deep research by NinjaTech AI powered by Cerebras: ‣ 1-2min for full answer instead of 10min ‣ 5x faster than o3, Gemini Pro etc. ‣ Same accuracy as measured by GAIA
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Introducing SuperNinja – the world’s fastest deep research by NinjaTech AI powered by Cerebras: ‣ 1-2min for full answer instead of 10min ‣ 5x faster than o3, Gemini Pro etc. ‣ Same accuracy as measured by GAIA

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Cerebras is officially public. A milestone for one of the most important AI infrastructure companies in the age of inference. We invested 8 to 9 years ago on a long shot. Proud of Andrew Feldman and the entire team for pulling it off. Congratulations!
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Cerebras is officially public. A milestone for one of the most important AI infrastructure companies in the age of inference. We invested 8 to 9 years ago on a long shot. Proud of Andrew Feldman and the entire team for pulling it off. Congratulations!

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Our coding workflows were designed to accommodate slow inference. OpenAI's Codex Spark powered by Cerebras changes the game. Here's how we make the most out of 1,200 tokens per second, with Sarah Chieng.
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Our coding workflows were designed to accommodate slow inference. OpenAI's Codex Spark powered by Cerebras changes the game. Here's how we make the most out of 1,200 tokens per second, with Sarah Chieng.

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🚨 Cerebras Inference is now 3x faster: Llama3.1-70B just broke 2,100 tokens/s - 16x faster than the fastest GPU solution - 8x faster than GPUs running Llama *3B* - It's like the perf of a new hardware generation in a single software release Available now at
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🚨 Cerebras Inference is now 3x faster: Llama3.1-70B just broke 2,100 tokens/s - 16x faster than the fastest GPU solution - 8x faster than GPUs running Llama *3B* - It's like the perf of a new hardware generation in a single software release Available now at

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Multi-LoRA is in private preview on Cerebras Inference. Deploy one base model alongside a library of LoRA adapters. Switch between them per request, with no reloading, no separate deployments, and no latency cost. Available now for dedicated endpoint users. Reach out to your account rep to get access.
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Multi-LoRA is in private preview on Cerebras Inference. Deploy one base model alongside a library of LoRA adapters. Switch between them per request, with no reloading, no separate deployments, and no latency cost. Available now for dedicated endpoint users. Reach out to your account rep to get access.

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🚨 BREAKING: NVIDIA JUST announced roadmap for physical AI, robotics and national-scale AI factories. Here’s a breakdown of the top important announcements: 🧵👇 1. DeepSeek R1 is now 4x faster, setting the standard for AI in inference and reasoning.

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Cerebras and Mayo Clinic are proud to announce a new state-of-the-art foundation model for genomics. The breakthrough was made possible by combining Mayo Clinic's extensive patient data with the Cerebras AI platform, training on over a trillion tokens to create complex genomic models that can guide personalized treatment decisions. Read more:
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Cerebras and Mayo Clinic are proud to announce a new state-of-the-art foundation model for genomics. The breakthrough was made possible by combining Mayo Clinic's extensive patient data with the Cerebras AI platform, training on over a trillion tokens to create complex genomic models that can guide personalized treatment decisions. Read more:

Cerebras

44,578 просмотров • 1 год назад

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?
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MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?

Ricardo

28,088 просмотров • 8 месяцев назад