Fireworks AI

Fast open-model inference with fine-tuning

LLM API $0.20-$0.90 per M tokens
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What It Is

Fireworks AI specializes in high-throughput inference for open-source models, with particular strength in serving agent workloads that require rapid tool calling and multi-step reasoning. Built by ex-Meta engineers who worked on PyTorch and ML infrastructure.

How It Works

Fireworks runs open models (Llama, Mixtral, DeepSeek, Qwen, FireFunction — their own function-calling fine-tune) on their custom inference stack. Their FireFunction model is specifically optimized for tool calling, which matters for agent applications. They also offer 'compound AI' patterns — ensembles of small and large models working together — for cost-optimized production.

Pricing Breakdown

Llama 3.1 70B: $0.90 per M tokens. FireFunction V2: $0.90. DeepSeek V3: $0.90. Fine-tuning with LoRA: $0.50-$1 per million training tokens. Dedicated deployments on request.

Who Uses It

Cursor, Notion AI, Quora, Upstage, and many AI-first startups. Popular for agentic workloads specifically.

Strengths & Weaknesses

✓ Strengths

  • Sub-second latency
  • Managed fine-tuning
  • Compound AI patterns
  • FireFunction for tool use

× Weaknesses

  • Less model variety than Together
  • US-focused infra
  • Less transparent pricing

Best Use Cases

Production deploymentsFine-tuningAgent inferenceFunction calling

Alternatives

Groq
World's fastest LLM inference
Together AI
Open-model hosting and fine-tuning
Replicate
Run open-source models via API
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