Fireworks

Fireworks AI builds foundational training and inference infrastructure for specialized intelligence, led by engineers with deep experience in large-scale ML systems and contributors associated with PyTorch. The company focuses on turning open models into production-grade, cost-efficient solutions for agents, coding, chat, and enterprise RAG.

Fireworks is an end-to-end platform for training and serving high-performing LLMs and multimodal models. It provides a drop-in, OpenAI- and Anthropic-compatible API with multi-provider routing, plus a Training API that spans guided jobs, configuration-led runs, and fully custom RL or supervised pipelines. Checkpoints promote to production in seconds on the same infrastructure, minimizing friction between experimentation and serving. Serverless, on-demand, and reserved tiers let teams balance latency, throughput, and cost, while the model library exposes popular open models tuned for quality and efficiency. The production engine is optimized across the stack for consistent latency and high token throughput, supporting agent, coding, RAG, and evaluation workloads. Fireworks also supports adapter-based fine-tuning, including multi-LoRA workflows and long-context variants, alongside priority and fast serving queues with per-token billing. The result is predictable performance and materially lower end-to-end coding and serving cost.