Cerebras Cloud

Cerebras Cloud is the fastest available inference for Llama 3.1/3.3 70B — regularly benchmarking at 1000-2100 tokens/second, compared to 50-100 tokens/second on typical GPU inference. The Wafer-Scale Engine is a custom chip architecture designed for linear algebra at scale; the result is dramatically faster inference for the models it supports. For agents where speed matters (real-time conversational AI, streaming responses, high-throughput batch processing): Cerebras delivers 10-20x throughput advantage over GPU inference for supported models. OpenAI-compatible API makes adoption trivial — change base_url and API key. Limited model catalog (Llama 3.1 8B/70B, Llama 3.3 70B, Qwen 3 32B) but covers common open-source choices. Generous free tier. Confidence is docs-derived.

OpenAI-compatible API at api.cerebras.ai/v1. POST /chat/completions with {model: "llama3.1-70b", messages: [...], stream: true/false, max_tokens, temperature, ...}. Available models: llama3.1-8b, llama3.1-70b, llama3.3-70b, qwen-3-32b. GET /models lists available models. Streaming: SSE format identical to OpenAI. Drop-in: client = openai.OpenAI(api_key="csk-...", base_url="https://api.cerebras.ai/v1"). Function calling supported on Llama 3.3 70B. Context window: 128k tokens for Llama 3.1/3.3 70B.

API key auth: Authorization: Bearer {api_key} (csk- prefix). Keys from inference.cerebras.ai → API Keys. Account-scoped. HTTPS enforced. No OAuth2. Credit-based billing: per-token pricing, prepaid credits. Free tier: generous token allowance for new accounts. Rate limiting: per-key tokens-per-minute and requests-per-minute limits. No per-model key scoping.

Standard HTTP status codes; OpenAI-compatible error format. 429 on rate limit (Retry-After header included). 400 for invalid model name or malformed request. Streaming: SSE with [DONE] sentinel. Cerebras hardware is purpose-built for inference — reliability is high under normal load. Service uptime at status.cerebras.ai. Context length enforcement: 400 error if input + max_tokens exceeds context window. Model catalog is deliberately limited — Cerebras optimizes deeply for each supported model.

inference-docs.cerebras.ai covers API reference, model list, function calling guide, and Python SDK quickstart. Getting started: create account (free tier), generate API key, first inference call in under 2 minutes using Cerebras Python SDK (cerebras-cloud-sdk) or OpenAI client with base_url override. Python SDK: from cerebras.cloud.sdk import Cerebras; client = Cerebras(); response = client.chat.completions.create(...). Community via Cerebras Discord and developer community. Documentation is concise and well-structured given the focused product scope.