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Cerebras Inference

Run Llama 70B at 1,800 tokens per second — 20x faster than GPU alternatives. The only inference provider where speed itself is the competitive moat.

Models
4.7freemium

Cerebras Inference — the verdict: Developers building real-time voice agents or interactive applications where inference speed is the bottleneck Cerebras Inference has one story: speed. Pricing: Free tier available / Pay-per-token. Last reviewed: August 2026.

Best For

Developers building real-time voice agents or interactive applications where inference speed is the bottleneck

Standout Feature

Purpose-built wafer-scale chips deliver roughly 20 times faster inference than typical GPU-based providers

Verdict

The fastest inference available by a wide margin, the model selection is a curated set, not the full open-source catalog.

Alternatives

Overview

Cerebras runs LLMs on purpose-built wafer-scale chips that achieve 1,800+ tokens per second — roughly 20x faster than GPU-based inference providers for the same model. The speed difference makes real-time voice agents, interactive code generation, and sub-second RAG pipelines practical for the first time. Supports Llama 3.1 70B and 405B, Llama 3.3 70B, and DeepSeek R1 via a free-tier API.

Our Take

Cerebras Inference has one story: speed. Running Llama 70B at roughly 1,800 tokens per second, about 20 times faster than GPU-based providers, is a category difference that unlocks real-time voice agents, sub-second RAG responses, and interactive code generation that actually feel instant. The free tier is substantive enough to evaluate real workloads. The tradeoff is breadth: the model selection is a curated set, not the full open-source catalog, and the purpose-built hardware means no custom fine-tuning support. If inference speed is the actual bottleneck in your application, evaluate Cerebras first. If you need a wide model selection, look elsewhere.

Key Features

  • 1,800+ tokens/second on Llama 3.1 70B — fastest available
  • Wafer-scale chip architecture eliminates inter-chip communication overhead
  • Supports Llama 3.1, 3.3, DeepSeek R1, and Qwen models
  • OpenAI-compatible API with streaming support
  • Free tier for prototyping with no credit card required
  • Real-time performance suitable for voice and interactive applications
Pros
  • Fastest inference in the industry by a wide margin
  • Free tier is genuinely useful, not just a trial
  • OpenAI-compatible — drops into existing code immediately
Cons
  • Model selection is limited to a curated set, not the full open-source catalog
  • Purpose-built hardware means no custom model fine-tuning support
  • Very high throughput can mask context window limitations

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