Fireworks AI
Free tierThe fastest inference platform for generative AI — train, tune, and deploy open models at production scale.
Key strengths
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Recent changes
- Models updated: Multiple open-source models (DeepSeek, Llama, Mistral, Qwen, GLM, Kimi, Gemma, etc.) plus closed-model API compatibility (OpenAI, Anthropic)
- Plans updated: Serverless inference billed per token (input/output/cached); embeddings from $0.008/1M tokens; training from $0.50/1M tokens (LoRA SFT, models up to 16B); on-demand GPU from $8.00/hr (H100) to $20.00/hr (GB300).
- Starting price: $0.07/mo → $0.008/mo
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Fireworks AI — Documentation & Integration Notes
API Access: Fireworks AI exposes a REST API for inference, fine-tuning, and embeddings. It is fully compatible with the OpenAI and Anthropic API schemas, enabling drop-in migration with minimal code changes.
Supported model families: DeepSeek, Llama, Mistral, Qwen, GLM, Kimi, Gemma, and others from the open-source ecosystem.
Pricing breakdown (as documented):
| Resource | Rate |
|---|---|
| Embeddings | From $0.008 / 1M tokens |
| Serverless inference | Per input / output / cached token (usage-based) |
| LoRA SFT training (up to 16B) | From $0.50 / 1M tokens |
| On-demand GPU — H100 | $8.00 / hr |
| On-demand GPU — GB300 | $20.00 / hr |
Key integration points:
- Azure — cloud infrastructure integration
- Cursor / Sourcegraph — code intelligence tooling
- Vercel — frontend/serverless deployment workflows
- Notion / UiPath / Gumloop — enterprise automation and productivity
- Quora — consumer AI application layer
Deployment architecture:
- Serverless: auto-scaled, no GPU reservation required, billed per token.
- On-demand: dedicated GPU instances for consistent throughput and latency SLAs.
- Multi-region: supported for latency optimization and data residency requirements.
- Multi-LoRA: serve multiple fine-tuned adapters from a single base model deployment.
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