Cerebras vs CoreWeave

Models run on the Cerebras Wafer-Scale Engine, which keeps model weights in on-chip SRAM to reach published speeds in the thousands of tokens per second

Chat Completions and Completions endpoints at api.cerebras.ai/v1, usable from the OpenAI SDKs or the Cerebras Python and TypeScript SDKs

Public endpoints serve unmodified open-weight models such as OpenAI GPT OSS and Qwen, with a documented policy of no pruning on hosted models

Configurable reasoning effort, streaming, structured outputs, parallel tool calling, and prompt caching across the catalog

Vision-capable models accept PNG and JPEG images alongside text

Private, provisioned endpoints on reserved capacity with fine-tuning, weight management, and additional model families, arranged through sales

Purpose-built AI-native platform with Kubernetes-native developer experience

First-to-market access to the latest NVIDIA GPUs including Hopper (H100, H200, GH200) and Blackwell/Blackwell Ultra (GB200 NVL72, GB300 NVL72, HGX B200, HGX B300)

Unified security, talent services, and observability platform for large-scale AI operations, including fleet and node lifecycle controllers

HPC Interconnect with GPUDirect RDMA over InfiniBand for GPU-to-GPU communication, plus VPCs and Direct Connect private links via Equinix and Megaport

Managed Slurm running on Kubernetes for batch and burst training workloads

S3-compatible AI Object Storage, POSIX distributed file storage, single-tenant VAST clusters, and local ephemeral storage on GPU nodes