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Fireworks AI vs Together AI

Fireworks AITogether AI

Bottom line: Fireworks AI for teams shipping production AI features; Together AI for cost-conscious teams on open models.

Fast, production inference for open and custom models.

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Inference, fine-tuning, and GPU clusters for open models.

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Votes00
PricingFreemiumFreemium
CategoryCodingCoding
Tags
inferencellm-apifine-tuningenterpriselow-latency
inferencefine-tuninggpu-cloudopen-sourcellm-api
Best for
  • Teams shipping production AI features
  • Companies hosting custom models
  • Builders of agents and compound AI systems
  • Cost-conscious teams on open models
  • ML teams that fine-tune
  • Startups scaling inference volume
Pros
  • Optimized low-latency inference
  • Supports custom and fine-tuned models
  • Production features like function calling and structured output
  • OpenAI-compatible API
  • Dedicated deployments for consistent performance
  • Large catalog of open and open-weight models
  • Competitive per-token pricing
  • Fine-tuning with weight ownership
  • Dedicated GPU clusters for scale
  • OpenAI-compatible API
Cons
  • Best value is at production scale, not hobby use
  • Per-model pricing varies and needs modeling
  • You evaluate open-model quality and safety
  • Dedicated deployments add cost and planning
  • Less generous free usage than some rivals
  • Broad pricing surface across several product lines
  • You own quality and safety evaluation of open models
  • Dedicated clusters require commitment and planning
  • Less turnkey than closed frontier APIs
  • Model catalog and prices change over time

Comparison generated from each tool's listing. Add or remove tools above to change it.