📖 The AI Tool Bible

Fireworks AI vs Together AI

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Fireworks AI
Fine-tuning
Together AI
Fine-tuning
TaglineProduction inference and fine-tuning platform for open-source LLMs, tuned for speed and enterprise economics.Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).
CategoryFine-tuningFine-tuning
PricingFreemium· Free signup credits; pay-per-token from ~$0.14/M in; enterprise reserved capacity on requestPaid· Pay-per-token; fine-tuning per-token
ModelMulti-model (DeepSeek, Qwen, GLM, Kimi, Gemma, Minimax, others)Llama / Mistral / Qwen / DeepSeek and others
Editorial score—8.6 / 10
Use cases
llm-fine-tuningserverless-inferencemulti-lora-servingcode-assistantsagentic-systems
open modelsfine-tuninginference
Pros
  • OpenAI- and Anthropic-compatible APIs against open-weight models
  • Strong fine-tuning + multi-LoRA hosting on a shared base
  • Serverless, on-demand, and reserved-capacity tiers cover most load shapes
  • Used in production by Cursor, Sourcegraph, Vercel, Notion
  • Wide open-model catalogue
  • Competitive inference pricing
  • Fine-tune + serve in one place
  • Dedicated endpoints for production
Cons
  • Platform itself is proprietary despite hosting open models
  • Per-token pricing can beat DIY GPUs at low volume but not at very high steady load
  • Model catalog churns fast; today's best price/perf may not be tomorrow's
  • Latency varies by model
  • Less polish than OpenAI
Websitefireworks.aiwww.together.ai
Pick Fireworks AI if
  • ✅ OpenAI- and Anthropic-compatible APIs against open-weight models
  • ✅ Strong fine-tuning + multi-LoRA hosting on a shared base
  • ✅ Serverless, on-demand, and reserved-capacity tiers cover most load shapes
  • ✅ Used in production by Cursor, Sourcegraph, Vercel, Notion
Pick Together AI if
  • ✅ Wide open-model catalogue
  • ✅ Competitive inference pricing
  • ✅ Fine-tune + serve in one place
  • ✅ Dedicated endpoints for production
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