Skip to main content
Cerebras runs Llama models on its wafer-scale chips and delivers inference speeds well beyond anything available from GPU-based providers — frequently over 1000 tokens per second. It’s the right pick when latency is the dominant constraint: real-time customer support, voice agents, autocomplete-style UIs, and high-throughput agent swarms.

Installation

Environment Setup

Get an API key at cloud.cerebras.ai.

Quick Start

Every Cerebras model uses the cerebras/ prefix:

Model Names

Speed-Critical Use Cases

Voice Agent Loop

Cerebras’s speed is what makes real-time voice agents feel natural — the model can respond in tens of milliseconds:

High-Volume Classification

When you need to process thousands of items per minute:

Streaming

Streaming on Cerebras feels essentially instant:

Massive Parallel Agent Swarms

Cerebras’s speed compounds in multi-agent setups — 20 agents in parallel can still finish in a couple seconds:

Tool Use

Cerebras’s Llama models support function calling:

Production Defaults

Next Steps