WorkflowsApr 8, 2026·2 min read

Cerebras — Fastest LLM Inference for AI Agents

Ultra-fast LLM inference at 2000+ tokens/second. Cerebras provides the fastest cloud inference for Llama and Qwen models with OpenAI-compatible API for instant AI responses.

AG
Agent Toolkit · Community
Quick Use

Use it first, then decide how deep to go

This block should tell both the user and the agent what to copy, install, and apply first.

pip install cerebras-cloud-sdk
from cerebras.cloud.sdk import Cerebras

client = Cerebras(api_key="...")

response = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "Explain quantum computing"}],
)
print(response.choices[0].message.content)

Or use OpenAI SDK:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.cerebras.ai/v1",
    api_key="...",
)
response = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "Hello"}],
)

What is Cerebras Inference?

Cerebras provides the fastest cloud LLM inference available — 2000+ tokens per second for Llama 3.3 70B, roughly 10x faster than traditional GPU inference. Built on Cerebras' custom Wafer-Scale Engine (WSE) chips, it delivers near-instant responses. OpenAI-compatible API means you can swap in Cerebras as a drop-in replacement for any OpenAI-based application.

Answer-Ready: Cerebras is the fastest cloud LLM inference — 2000+ tokens/sec for Llama 70B (10x faster than GPU). Custom wafer-scale chips. OpenAI-compatible API for drop-in replacement. Supports Llama 3.3, Qwen 2.5, DeepSeek. Free tier available.

Best for: Applications needing ultra-low latency AI responses. Works with: Any OpenAI-compatible tool, Claude Code (via Bifrost), LangChain. Setup time: Under 2 minutes.

Speed Comparison

Provider Llama 3.3 70B Speed Relative
Cerebras 2,100 tok/s 10x
Groq 750 tok/s 3.5x
Together AI 400 tok/s 2x
AWS Bedrock 200 tok/s 1x
OpenAI (GPT-4o) 150 tok/s 0.7x

Supported Models

Model Context Speed
Llama 3.3 70B 8K 2,100 tok/s
Llama 3.1 8B 8K 4,500 tok/s
Qwen 2.5 32B 8K 2,800 tok/s
DeepSeek R1 8K 1,800 tok/s

Features

1. OpenAI-Compatible API

# Drop-in replacement — just change base_url
client = OpenAI(base_url="https://api.cerebras.ai/v1", api_key="...")

2. Streaming

stream = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "Write a story"}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content, end="")

3. Tool Calling

response = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "What's the weather?"}],
    tools=[{
        "type": "function",
        "function": {
            "name": "get_weather",
            "parameters": {"type": "object", "properties": {"city": {"type": "string"}}},
        },
    }],
)

Pricing

Tier Requests Price
Free 30 req/min $0
Developer Higher limits Pay-as-you-go
Enterprise Custom Custom

FAQ

Q: Why is it so fast? A: Cerebras uses custom wafer-scale chips (WSE-3) — a single chip larger than a GPU that eliminates memory bandwidth bottlenecks.

Q: Can I use it with Claude Code? A: Not directly (Claude Code uses Claude). Use Bifrost CLI to route Haiku-tier requests to Cerebras for speed.

Q: How does quality compare? A: Same models, same quality. Cerebras runs the exact same Llama/Qwen weights — only inference speed differs.

🙏

Source & Thanks

Created by Cerebras.

cerebras.ai/inference — Fastest LLM inference

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