Cerebras
Wafer-scale AI chip delivering the fastest inference and training performance
Our Take
Cerebras leads on raw speed with its wafer-scale approach — a single 300mm wafer with 4 trillion transistors and 44GB on-chip SRAM. Independent benchmarks show ~6× faster than Groq on large models. The March 2026 AWS partnership is transformative: disaggregated inference through Bedrock where Trainium handles prefill and Cerebras handles decode. Unlike Groq, Cerebras supports both training and inference. An IPO targeting Q2 2026 at an $8.1B valuation signals maturation. If you need absolute peak inference speed, especially on larger models, Cerebras is the leader.
Pros
- + Fastest inference via wafer-scale engine
- + Supports both training and inference
- + Handles 405B+ parameter models
- + AWS Bedrock integration
Cons
- - No free tier
- - Limited model catalog compared to GPU providers
- - Manufacturing complexity limits scale
- - Premium pricing vs. GPU-based alternatives
Details
- Pricing Model
- usage-based
- Starting Price
- ~$0.60/M tokens (Llama 70B)
- Self-Hosted
- No
- Cloud Hosted
- Yes
- Founded
- 2016
Best For
- • Maximum inference speed
- • Large model inference (405B+)
- • Training and inference on custom silicon
- • Enterprise-scale AI workloads
Integrations
OpenAI API compatible AWS Bedrock Llama DeepSeek
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