RealFeedApp Kimi K3 scores 88.3% on Terminal-Bench 2.1
Cerebras split the 3-trillion parameter Kimi K3 model across multiple WSE-3T wafers to achieve inference speeds of 1000–2000 tokens per second.
- Field
- hardware and chips
- What they did
- Cerebras demonstrated how to run trillion-parameter models on its chips by splitting them across multiple wafers to fit the model weights into on-chip memory.
- Why it matters
- This enables processing requests at speeds of 1000–2000 tokens per second, which is necessary for working with very large language models.
#cerebras#llm#trillion-parameter#wse-3t#inference
