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Fireworks AI Docs

Official Fireworks AI documentation for inference, deployments, training, Fireworks Nexus, APIs, SDKs, and CLI tools.

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For agents: Fireworks AI docs for serverless model inference, dedicated deployments, fine-tuning (SFT/DPO), per-token pricing, APIs, SDKs and CLI tools.

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# Fireworks AI Docs

> Official Fireworks AI documentation for inference, deployments, training, Fireworks Nexus, APIs, SDKs, and CLI tools.

- [Build with Fireworks AI](https://docs.fireworks.ai/getting-started/introduction.md): Fast inference and training for open-source models on Fireworks AI, covering serverless APIs, dedicated deployments, fine-tuning, and multi-modal workflows.
- [Fireworks Nexus](https://docs.fireworks.ai/getting-started/nexus.md): Connect coding tools, agents, applications, and gateways to open models and Nexus Auto.
- [Training Overview](https://docs.fireworks.ai/fine-tuning/finetuning-intro.md): Choose managed SFT, DPO, or ORPO, or run RL on the Training API, then pick serverless or dedicated infrastructure.
- [Serverless Quickstart](https://docs.fireworks.ai/getting-started/quickstart.md): Make your first serverless API call with GLM 5.3 Flash: create an API key and send a chat completion with curl or the Python SDK.
- [Deployments Quickstart](https://docs.fireworks.ai/getting-started/ondemand-quickstart.md): Deploy open-source models on dedicated GPUs on Fireworks in minutes, covering deployment creation, GPU sizing, and calling the endpoint from the API.
- [Which model should I use?](https://docs.fireworks.ai/guides/recommended-models.md): Pick the best Fireworks open-weight model for chat, coding, vision, embeddings, and agents, or migrate off Claude, GPT, and Gemini to comparable open models.
- [Concepts](https://docs.fireworks.ai/getting-started/concepts.md): Learn the core concepts for the Fireworks AI platform, including serverless inference, dedicated deployments, models, fine-tuning, and API keys.
- [Serverless Inference Overview](https://docs.fireworks.ai/serverless/overview.md): How Serverless inference works on Fireworks: serverless modes, per-token billing, request headers, prompt caching, model lifecycle, and when to pick Serverless.
- [Serverless Modes](https://docs.fireworks.ai/serverless/serverless-modes.md): Compare Standard, Priority, and Fast serverless modes on Fireworks Serverless to choose the right tradeoff between cost, latency, and throughput.
- [Serverless Pricing](https://docs.fireworks.ai/serverless/pricing.md): Per-token serverless pricing for text, vision, and embedding models on Fireworks, including Standard, Priority, and Fast serverless mode rates.
- [Reserved Throughput](https://docs.fireworks.ai/serverless/reserved-throughput.md): Reserve dedicated serverless throughput on Fireworks backed by an SLA, with guaranteed rate limits, additive capacity, and predictable per-token billing.
- [Serverless Rate Limits](https://docs.fireworks.ai/serverless/rate-limits.md): How adaptive rate limits work on Fireworks serverless inference: bounds, adjustment logic, and how RPS and TPS grow and shrink with your recent usage patterns.
- [US-only Serverless](https://docs.fireworks.ai/serverless/us-only-serverless.md): Run Fireworks Serverless inference exclusively on US infrastructure using US-scoped
…

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