Fireworks AI is a generative AI inference platform built by former PyTorch engineers to deliver the fastest, most reliable production-grade serving of open-source and custom models. The platform offers serverless inference across 400+ models—including DeepSeek, Llama, Qwen, GLM, Gemma, MiniMax, and OpenAI-compatible variants—with pay-per-token pricing that starts at $0.10 per 1M tokens for small models and scales up to $0.90 per 1M tokens for large 70B-parameter models. Fireworks emphasizes ultra-low latency, with customers reporting 3x faster response times and tail latency reduced from 2 seconds to 350 milliseconds. Beyond inference, Fireworks offers a full Tune stack including LoRA, supervised fine-tuning, preference tuning, reinforcement learning, and quantization-aware training, with fine-tuned models served at base model pricing. The platform's on-demand GPU deployments support H100/H200 at $7/hour, B200 at $10/hour, and B300 at $12/hour, with elastic auto-scaling tied to real traffic patterns. Enterprise customers benefit from SOC 2 Type II, HIPAA, GDPR, and ISO certifications, plus bring-your-own-cloud or Fireworks-hosted deployment options. Backed by Jensen Huang's endorsement as 'the TSMC of AI Factories,' Fireworks has grown rapidly with $315M ARR by early 2026 and 10,000+ enterprise customers, becoming a top choice for developers and enterprises seeking high-performance, cost-efficient inference at scale.