Cerebras vs Vast.ai

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

Prices set by supply and demand across the platform with no list prices or hidden fees

GPU Cloud for full control, Serverless for zero-ops inference, Clusters for large-scale training

CLI, Python SDK, and REST API for programmatic GPU provisioning, installed together via a single package

API-native workflow intended for AI agents to search, procure, and release compute autonomously

Prebuilt templates for popular open-source models, plus custom templates any GPU can run with one click

Scale from $5 to 20,000 GPUs across 40+ data centers without contracts or minimums