Cerebras
@cerebras • 79,061 subscribers
The world's fastest AI inference and training. Try the latest open models at: https://t.co/jREGhLI2nj
Shorts
Videos
Previewing Ultrafast mode for OpenAI's GPT 5.6 Sol, powered by Cerebras. GPT-5.6 Sol Ultrafast generates responses at up to 750 tokens per second. That's the full, GPT-5.6-Sol model -- up to 14× faster than the same model on Standard processing. It speedran Humanity’s Last Exam in 11h 11m, nearly 7× faster than Claude Fable 5 with comparable accuracy.
Cerebras1,292,974 Aufrufe • vor 2 Monaten
GLM 4.7 is one of the strongest open-source coding models available—but most developers aren't prompting it correctly. We put together 10 rules to help you get the most out of it: - Front-load instructions (it has a strong recency bias) - Use firm language: "must" and "strictly" > soft suggestions - Break complex tasks into smaller steps - Disable reasoning for simple tasks, enable it for hard ones - Use critic agents for code review, QA, and validation - Pair it with a frontier model for the hardest 10% of workloads - and more… GLM 4.7 hits 96% on Tau² Bench and 86% on GPQA Diamond. At 1,500 tokens/sec on Cerebras, it's 20x faster than closed-source alternatives on GPUs.
Cerebras633,658 Aufrufe • vor 8 Monaten
Right now, when you send a query to an LLM, it gets decrypted on the server. The LLM sees your data in plain text. Prof. Ajay Joshi (BU, CipherSonic AI ) on fully homomorphic encryption, which may be key for the future of AI privacy: how we can compute on data without ever decrypting it. The catch: it's a brutally memory-bound workload. Exactly the bottleneck wafer-scale was built to solve.
Cerebras293,785 Aufrufe • vor 4 Monaten
Cyber attackers move fast, so defenders have to move faster 🚨 Analyzing an unfamiliar file is an everyday security workflow: analysts identify its behavior and indicators, then search for them across the environment before the threat spreads. Powered by Cerebras, GPT-5.6 Sol Ultrafast completes the analysis in 58 seconds, versus 4 minutes and 43 seconds for Sol Standard on GPUs-- helping defenders contain threats before attackers can advance.
Cerebras67,397 Aufrufe • vor 26 Tagen
Ultrafast mode for GPT-5.6 Sol is now in limited preview, powered by Cerebras. We gave OpenAI's GPT-5.6 Sol the same prompt on Ultrafast and Standard: build a financial terminal-style dashboard for analysts. Ultrafast: 1 min 50 seconds Standard: 12 min 20 seconds Same result, nearly 7x faster.
Cerebras146,136 Aufrufe • vor 2 Monaten
"You now have new surface area to expose the benefits of the silicon in new ways. We had some really amazing results when doing this over a huge amount of different silicon. Cerebras was unbelievably good. We could actually not only improve the speed by a significant amount in these long-context reasoning problems, we also found that we could also make them very cost-effective because we're being efficient with the tokens." — Danyal, co-founder of Callosum, in conversation with our Andy Hock on the new Cerebras-Callosum partnership.
Cerebras88,821 Aufrufe • vor 1 Monat
“We coined this term called the semi-async valley of death.” At Cerebras Supernova, Silas Alberti unpacked why coding tasks that take 1 to 3 minutes break flow, and how Cerebras powers Cognition’s SWE-1.7 in Devin at up to 1,000 tokens per second to keep developers in the loop.
Cerebras89,992 Aufrufe • vor 1 Monat
"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.
Cerebras132,895 Aufrufe • vor 2 Monaten
OpenAI Codex-Spark powered by Cerebras You can now just build things faster—at 1,000 tokens/s.
Cerebras287,979 Aufrufe • vor 8 Monaten
Some of our top customers are still choosing Llama 3.1 8B. For a while, we jumped to whatever hottest, latest model was taking up our twitter feed. 🙈 But as we are quickly realizing, to create a SOTA product, you need a model that fits your exact use case. Here’s what our customers tell us: > a lot of the legwork is actually around prompting > there’s an art to selecting and combining multiple models > benchmarks only show part of the picture. you have to understand the unique quirks of each model. Especially as model releases become more and more frequent, we need a clear way to evaluate new models. We have to break free of the naive trend to migrate to the ‘latest and greatest’. And you can easily achieve this using tools like Cerebras and Braintrust to swap models safely (without breaking production).
Cerebras346,446 Aufrufe • vor 10 Monaten