ModelRefs / Fireworks AI — AI Glossary
Fireworks AI — AI Glossary
A fast LLM inference platform offering OpenAI-compatible APIs for open models with serverless and dedicated deployment options.
Overview
Fireworks AI provides inference for LLaMA, Mixtral, FireLLaVA, and other open models with optimized CUDA kernels and speculative decoding. Features: function calling, grammar-constrained generation (JSON Schema enforcement), serverless and reserved capacity, and fine-tuning. Competes on throughput, latency, and pricing against Together AI.
Reference details
| Topic | infrastructure |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
Sits in the same category as Together, Replicate and Groq — hosted open-weight inference behind an OpenAI-compatible API — with serverless and dedicated deployment as the axis it emphasises. Serverless means paying per token with cold-start variance; dedicated means paying for reserved capacity with predictable latency. That choice, not the vendor, is usually what determines whether the deployment meets its latency target.
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Frequently asked questions
What is Fireworks AI?
A fast LLM inference platform offering OpenAI-compatible APIs for open models with serverless and dedicated deployment options.
What concepts are related to Fireworks AI?
Closely related concepts include together ai, groq, openai compatible.