We raised $250M in Series C funding at a $2.2B valuation, led by a16z. Exa is a search lab organizing the web's data for agents.

Cerebras is now running Kimi K2.6 – a trillion parameter model – in enterprise trials. At ~1,000 tokens/s, this is the fastest frontier model performance ever measured by Artificial Analysis @ArtificialAnlys.

I've been working on a new LLM inference algorithm. It's called Speculative Speculative Decoding (SSD) and it's up to 2x faster than the strongest inference engines in the world. Collab w/ @tri_dao @avnermay. Details in thread.

🚀 Today we’re releasing FlashOptim: better implementations of Adam, SGD, etc, that compute the same updates but save tons of memory. You can use it right now via `pip install flashoptim`. 🚀 arxiv.org/abs/2602.23349 A bunch of cool ideas make this possible: [1/n]

Taalas Specializes to Extremes for Extraordinary Token Speed eetimes.com/taalas-specializ…

2 weeks ago, we rebuilt our entire product. "Browser automation" fell short of our mission to eliminate all repetitive knowledge work. The new Kaizen is the ultimate digital employee: always on, extremely capable, continually learning. Sign up for access in the tweet below.

InferenceX v2: NVIDIA Blackwell Vs AMD vs Hopper - Formerly InferenceMAX, GB300 NVL72, MI355X, B200, H100, Disaggregated Serving, Wide Expert Parallelism, Large Mixture of Experts, SGLang, vLLM, TRTLLM semianalysis.substack.com/p/…

OpenAI Codex-Spark powered by Cerebras You can now just build things faster—at 1,000 tokens/s.

sim the people, sim the world, join simile. they kick ass. @joon_s_pk @msbernst @percyliang @ElainaYallen @mihikapoor

The world’s most powerful data agent releases today. Sphinx 1.0 is here to power elite data teams.

Excited to announce today that my startup, @positron_ai, has closed a $230M Series B financing round at an over $1B valuation, co-led by great folks at @jumptrading, Arena, Unless Ventures, and strategic backing by @Arm! bloomberg.com/news/articles/…

OpenAI🤝Cerebras openai.com/index/cerebras-pa…

I've got something new for everyone. My first substack article! Not the one I planned to do first, but a fun one! I have made a handy calculator base on the DeepSeek v1 coefficients for finding optimal LR and batch sizes for dense LLMs.

Apologies that I haven't written anything since joining Thinking Machines but I hope this blog post on a topic very near and dear to my heart (reproducible floating point numerics in LLM inference) will make up for it!

🚀 Thrilled to announce our $9.5M funding round led by @buckymoore at @lightspeedvp, alongside an incredible group of investors from the Valley and New York. ✨ With this announcement, we’re also moving Sphinx Copilot -- the state-of-the-art AI agent for data science -- out of closed beta. It’s now available at sphinx.ai (with a generous free tier!). Our early partners have gone from raw data ➝ commercial insights in minutes instead of days. We can’t wait to see what the data community builds with Sphinx. 🌱 This is just the beginning for Sphinx. We’re redefining how AI works with data, from copilots to fully autonomous researchers and analysts. We're excited to keep building best-in-class machine intelligence for a new generation of data-driven innovation. sphinx.ai/blog/sphinx-launch…

alexander wang with yann lecun

memory-bound gf, compute-bound bf

presenting: big jeff's trainium hell

Cerebras just beat NVIDIA Blackwell Last week: Blackwell hit 1,000 t/s on Llama 4. Today: Cerebras hit 2,500 t/s on the same model, same benchmarks by @ArtificialAnlys Blackwell smoked Groq, AMD, Google – everyone. Only Cerebras stands – and we smoked Blackwell.