TokenMix Research Lab · 2026-04-24

Cerebras API Key: Access, Pricing, Speed Tests 2026

Cerebras API Key: Access, Pricing, Speed Tests 2026

Cerebras is the fastest LLM inference provider in 2026 — delivering 1,800+ tokens/second on Llama 3.3 70B thanks to their wafer-scale CS-3 chip architecture. Compared to typical GPU inference at 50-200 tok/s, Cerebras is 10-20× faster. This guide covers how to get a Cerebras API key (5-minute signup), pricing ($0.60-$3.90 per MTok depending on model size), supported models (Llama 3.3 70B, 405B, Qwen3, DeepSeek variants), speed benchmarks, and when it's worth paying more for the speed premium. Plus Cerebras vs Groq comparison. TokenMix.ai routes Cerebras alongside 300+ other models.

Table of Contents

Confirmed vs Speculation

Claim Status
Cerebras produces 1800+ tok/s on 70B Confirmed
CS-3 wafer-scale chip architecture Confirmed
Llama 3.3 70B / 405B available Confirmed
OpenAI-compatible API Yes
Free tier available Yes (rate-limited)
Faster than Groq Usually yes for same model
Price premium vs standard GPU inference Yes ~2-3×

Cerebras Signup (5 Minutes)

  1. Go to cloud.cerebras.ai
  2. Sign up with email
  3. Add billing (free tier starts, card required for production)
  4. Navigate to API Keys → create new
  5. Copy key (shown once)

First API call:

curl https://api.cerebras.ai/v1/chat/completions \
  -H "Authorization: Bearer $CEREBRAS_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.3-70b",
    "messages": [{"role":"user","content":"Hello"}]
  }'

Response returns in under 1 second thanks to high throughput.

Pricing by Model

Model Input $/MTok Output $/MTok Throughput
llama-3.3-70b $0.60 $0.60 1800 tok/s
llama-3.3-70b-instruct $0.60 $0.60 1800 tok/s
llama-3.1-405b $3.00 $3.90 969 tok/s
llama-3.1-8b $0.10 $0.10 2200 tok/s
qwen-3-32b $0.50 $0.50 1200 tok/s
deepseek-r1-distill-70b $0.60 $2.40 1500 tok/s

Free tier: limited requests/day on smaller models. Check dashboard for current limits.

Speed Benchmarks

Measured April 2026, Llama 3.3 70B on each provider:

Provider Throughput (tok/s) TTFT Hardware
Cerebras 1,800+ <100ms CS-3 wafer
Groq 550 <100ms LPU
Together.ai 150 200ms H100
Fireworks 180 150ms H100
OpenAI (GPT-5.4) ~80 300ms H100
Anthropic (Opus 4.7) ~60 400ms varies

Cerebras is 3× faster than Groq, 10× faster than H100-based inference.

For use cases where throughput matters (real-time voice, multi-agent loops with many turns, batch processing), speed compounds.

Cerebras vs Groq

Dimension Cerebras Groq
Speed (70B model) 1800 tok/s 550 tok/s
Pricing (70B) $0.60/$0.60 $0.59/$0.79
Supported models Llama, Qwen, DeepSeek distills Llama, Mixtral, Qwen
API maturity Production Production
Free tier Yes Yes (generous)
Custom silicon CS-3 wafer LPU
First-token latency <100ms <100ms

Pick Cerebras if: absolute speed is critical. Pick Groq if: slightly larger model catalog, comparable-ish speed, generous free tier. Both strong choices for speed-sensitive workloads.

When Speed Is Worth The Cost

Cerebras is more expensive than GPU-based inference (2-3× vs DeepSeek hosted). Worth it for:

  1. Real-time voice agents — sub-300ms full loop needs fast inference
  2. Multi-agent workflows — compound latency across 5+ LLM calls
  3. Interactive RAG — user expects fast response despite retrieval overhead
  4. Live coding assistance — inline completion speed directly affects UX
  5. High-concurrency batch — process 1000 queries faster per dollar due to throughput

Not worth for:

FAQ

Can Cerebras run Claude or GPT-4?

No. Cerebras hosts only open-weight models (Llama family, Qwen, DeepSeek distills, some Mistral). For Claude/GPT, use Anthropic/OpenAI direct or aggregator.

Is Cerebras's speed consistent under load?

Generally yes — wafer-scale architecture handles concurrency well. Peak hour slight degradation observed but throughput still 1500+ tok/s. More stable than some GPU-based providers.

What's the free tier limit?

Generous but rate-limited: ~1M free tokens/day on Llama 3.3 70B. Enough to prototype and test. For production, paid tier.

Does Cerebras support function calling / tool use?

Yes on Llama 3.3 70B and newer models. Standard OpenAI tool schema via OpenAI-compatible API.

How does speed feel subjectively in a chat app?

Instant. On a 500-token response, Cerebras finishes in ~0.3 seconds vs 5-10 seconds on GPU-based inference. Users can't read as fast as Cerebras generates.

Is 405B faster on Cerebras than 70B on others?

Yes — 405B at 969 tok/s beats most competitors' 70B speeds. Use Cerebras's 405B as the "quality + speed" combo when budget allows ($3/$3.90 per MTok).

Any Cerebras downsides beyond cost?

Smaller model catalog vs Anthropic/OpenAI. If you need Claude Opus 4.7 or GPT-5.4 specifically, Cerebras doesn't help. For open-weight routing, Cerebras is optimal.

Sources

By TokenMix Research Lab · Updated 2026-04-24