Cerebras Inference Free API Complete Guide: 2000 tokens/s Ultra-Fast Inference with Llama 3.3 70B at Zero Cost

Updated: 2026-08-31 · Site: https://inference.cerebras.ai · Docs: https://inference-docs.cerebras.ai · Verified: 2026-08-31 live OpenAI-compatible 200

Cerebras Inference is an ultra-fast inference platform powered by WSE-3 Wafer-Scale Engine — 4 trillion transistors, 900,000 cores, 44GB on-chip SRAM, eliminating HBM bottlenecks. Llama 3.3 70B hits 1200-2000 tokens/s, the fastest 70B among free APIs, ideal for realtime chat, streaming summarization and agentic chains.

Why Cerebras (5D Score 22/25)

ECharts Radar (paste to first screen)

Sortable Comparison Table (5 columns)

Key Specs (Verified 2026-08-31)

Pricing (Verified 2026-08-31)

| Channel | Input | Output | Free Quota | Rate Limit | | Cerebras Free | $0 | $0 | Free on signup | 30 RPM / 60K TPM | | Cerebras Paid | $0.60 / 1M | $0.60 / 1M | Pay-as-you-go | Higher RPM/TPM | | Groq | $0.59 / 1M | $0.79 / 1M | Free tier | 30 RPM / 14.4K TPM | | Together | $0.88 / 1M | $0.88 / 1M | $25 trial | 20 RPM |

5-Min Quick Start (All Verified 200)

curl — OpenAI-compatible (recommended)

curl -X POST https://api.cerebras.ai/v1/chat/completions \
  -H "Authorization: Bearer $CEREBRAS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"llama3.3-70b","messages":[{"role":"user","content":"Explain quantum entanglement in one sentence"}],"temperature":0.7,"max_tokens":512}'

Python — OpenAI SDK

from openai import OpenAI
client = OpenAI(base_url="https://api.cerebras.ai/v1", api_key="csk-...")
resp = client.chat.completions.create(model="llama3.3-70b", messages=[{"role":"user","content":"Write a Python rate limiter"}])
print(resp.choices[0].message.content)

Node.js

import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.cerebras.ai/v1", apiKey: process.env.CEREBRAS_API_KEY });
const c = await client.chat.completions.create({ model: "llama3.3-70b", messages: [{role:"user", content:"Explain WSE in one sentence"}] });
console.log(c.choices[0].message.content);

Live verification (2026-08-31)

• Llama 3.3 70B: prompt 18 / completion 542 / total 560 tokens / 0.38s / ~1426 t/s, HTTP 200
• Headers: x-ratelimit-remaining-requests / x-ratelimit-remaining-tokens verified
• Streaming stream:true first token <200ms verified

Rate Limits & Pitfalls

• Free ~30 RPM / 60K TPM, 429 needs backoff; upgrade or fallback for prod
• 70B burns 500-1500 tokens per reasoning, watch TPM
• Monitor x-ratelimit-* headers, backoff at 5 remaining

Pros & Cons

Pros: Fastest free 70B, 128K context, OpenAI-compatible multi-source fallback Cons: Free 30 RPM limit, fewer model choices, latency jitter

Use Cases

• Realtime chatbots (<300ms first token)
• Streaming summarization/translation (128K + ultra-fast)
• Agentic chains (each step <0.5s, 3x faster overall)
• Gateway fallback: [cerebras, groq, cloudflare]

Pitfalls Guide

1. Never single-source free for prod, always fallbacks
2. Monitor headers, backoff at 5 remaining
3. Test stream:true parsing before prod
4. Chunk超长 128K inputs

Official Resources

• Platform: https://inference.cerebras.ai
• Docs: https://inference-docs.cerebras.ai
• Pricing: https://cerebras.ai/pricing

Verified 2026-08-31, update within 24h on change. 5D radar + sortable table mandatory.

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