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Jul 1, 2026
Input modalities
Output modalities
Capabilities
131,072 tokens
Recent tweets and retweets from Cerebras
Talk to Gemma 4 31B with our voice app!
It sees and searches the web faster than you blink. Thanks to @cerebras’ ultra fast inference, the LLM is almost instantaneous.
The whole stack is fully open-source, and is a drop-in replacement for OpenAI's realtime API.
Demo:…
Watch the full interview: piped.video/LRpw1PAQxbc
In conversation with @MilksandMatcha for Cerebras's Big Chip Club, produced by @alyciazcary.
Link
Cerebras Big Chip Club: Logan Kilpatrick on why speed will define the next generation of AI products
Logan Kilpatrick — who…
"If you knew you could get that many tokens, you would build different products."
Logan Kilpatrick (@OfficialLoganK ,@GoogleDeepMind) on why fast inference doesn't just make AI faster. It changes what is possible to build.
@googlegemma's Gemma 4 is now on Cerebras, running…
We gave two agents the same task: “Find images matching this description.”
Both use Gemma 4 31B. One runs on Cerebras.
The other runs on GPUs.
You can see the difference.
Speed changes the product experience. What would you build if you didn't have to wait?
Video
I just ran Gemma 4 31B on @CerebrasSystems at 1,800+ tokens/sec and it's multimodal.
For context: that's 35x faster than a typical GPU endpoint, and the first token (reasoning included) lands in 1.5 seconds. This isn't a benchmark slide, I recorded the inference live.
Prompt…
Discuss this model
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