Key features
Core capabilities each platform advertises.
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- Wafer-scale inference chips
- Record-breaking inference speed
- Simple API deployment
- Optimized for large language models
- Custom silicon architecture
Updated March 10, 2026
Anyscale is the company behind Ray, the open-source distributed computing framework used by OpenAI, Uber, and Spotify for scaling AI workloads. Anyscale's platform provides managed Ray clusters for distributed training, batch inference, and model serving, making it easy to scale AI applications across hundreds of GPUs.
Cerebras builds the world's largest AI chips—wafer-scale processors that contain millions of cores on a single silicon wafer. The Cerebras CS-2 system delivers massive parallelism for AI training and ultra-fast inference for open-source models. Through Cerebras Inference, developers can access some of the fastest LLM inference speeds available, particularly for Llama models.
Core capabilities each platform advertises.
What each tool does well, and the limitations to keep in mind.
Pros
Cons
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