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AI Tool Comparison

Cerebras Inference vs Fireworks AI

A side-by-side breakdown to help you pick the right tool for your workflow.

Cerebras Inference logo

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
freemium
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Fireworks AI logo

Fireworks AI

Run Llama, Mixtral, and 50+ open-source models at production speed — 3–5x cheaper than OpenAI-equivalent APIs with the same SDK you're already using.

Models
freemium
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Bottom Line

Cerebras Inference edges ahead on rating (4.7 vs 4.6), but the right pick still comes down to which workflow you're running.

Choose Cerebras Inference if…

Coding

Choose Fireworks AI if…

Coding

AttributeCerebras InferenceFireworks AI
CategoryModelsModels
Pricingfreemiumfreemium
Pricing DetailFree tier available / Pay-per-tokenFree $1 credit / Pay-per-token from $0.20/M tokens
Rating4.74.6

Key Features

Cerebras Inference

  • 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

Fireworks AI

  • OpenAI-compatible API for instant drop-in replacement
  • 50+ open-source models including Llama, Mixtral, and Gemma
  • Compound AI system deployment (multiple models in one call)
  • Function calling and JSON mode across all supported models
  • Fine-tuning API for custom model specialization
  • Sub-100ms time-to-first-token on most models

Pros

Cerebras Inference

  • 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

Fireworks AI

  • Best-in-class latency for open-source model inference
  • Significantly cheaper than OpenAI at scale
  • OpenAI-compatible API means zero migration effort

Cons

Cerebras Inference

  • 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

Fireworks AI

  • Smaller model selection than OpenRouter
  • Fine-tuning has limited base model options vs dedicated platforms
  • Free credit is small — production workloads require billing setup

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