Fireworks Ai

Fireworks AI provides fast inference for open-source and custom AI models with an OpenAI-compatible API. For agents, the key value propositions are speed (among the fastest inference latencies for open-source models), OpenAI API compatibility (switch models without changing code), and model variety (Llama 3, Mixtral, Qwen, DeepSeek, and custom fine-tuned models). Function calling enables tool-use patterns with open-source models. JSON mode and grammar-constrained generation ensure structured output. The API supports chat completions, text completions, embeddings, and image generation. Fine-tuning lets agents create specialized models. For agents diversifying beyond OpenAI/Anthropic or needing fast open-source model inference, Fireworks is a strong option. The main consideration: model availability is curated — not every open-source model is available.

The API at api.fireworks.ai/inference/v1/ mirrors OpenAI's endpoints: /chat/completions, /completions, /embeddings. This compatibility means agents using OpenAI client libraries can switch to Fireworks by changing the base URL and API key. Model selection uses Fireworks model IDs (e.g., accounts/fireworks/models/llama-v3-70b-instruct). Function calling follows OpenAI's tool/function schema. JSON mode forces structured JSON output. Response format parameter enables grammar-constrained generation for custom output schemas. Streaming uses SSE (Server-Sent Events) like OpenAI. The API also provides model listing, fine-tuning job management, and deployment management for custom models. Batch API supports async processing for high-volume workloads. The OpenAI compatibility dramatically reduces integration effort for agents already using OpenAI.

API key authentication via Authorization: Bearer header. Keys are generated in the Fireworks dashboard. No fine-grained key scoping — keys grant full account access. No OAuth for third-party integrations. Usage is tracked per-account with pay-per-token pricing. Organization accounts support team access with role-based permissions. The auth model is identical to OpenAI's: simple API key, appropriate for the use case. No temporary credentials or key rotation mechanism beyond deleting and creating new keys. For agents, the familiar API key pattern means no new auth concepts to learn. The main consideration: API key security is the agent's responsibility — no IP restrictions or usage caps per key.

API errors follow OpenAI's format: JSON with error.type, error.message, and error.code. Standard HTTP status codes. Rate limits are generous and scale with account tier. 429 responses include retry guidance. Model-specific errors (context length exceeded, unsupported feature for a specific model) return descriptive messages. Streaming errors are delivered as SSE error events. The inference infrastructure uses optimized serving (FireAttention, speculative decoding) for low latency. Model availability is generally reliable — popular models have high uptime. Less popular or newly added models may have intermittent availability. Function calling reliability varies by model — larger models are more reliable at following tool schemas. For agents, implementing model fallback (try preferred model, fall back to alternative) is a good reliability pattern.

Documentation at docs.fireworks.ai covers API reference, model catalog, fine-tuning, and deployment guides. The API reference maps to OpenAI's documentation structure, which is familiar for most agent developers. The model catalog lists available models with capabilities, context lengths, and pricing. Function calling documentation specifies which models support tools. Fine-tuning documentation covers data preparation, job creation, and deployment. The documentation is focused and practical — less extensive than OpenAI's but adequate for the API surface. Code examples in Python and cURL cover common patterns. The main documentation gap: model-specific quirks and optimal prompting strategies aren't as well-documented as for first-party model providers. For agents, the model catalog and OpenAI migration guide are the key starting points.