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Fireworks AI

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Developer platform for fast serverless inference and training of open generative models, billed per token or GPU-second.

What it does

Fireworks AI is an inference and training platform for open-source generative models built by ex-PyTorch engineers. Developers can run popular open LLMs and vision, image and audio models via a serverless pay-per-token API, dedicated on-demand deployments or reserved capacity, and can fine-tune or run RL training that deploys to production quickly. It emphasizes high throughput and low latency at scale.

How to use: Users can start by running popular models via APIs, customize models for better performance, and build compound AI systems using FireFunction for tasks like RAG, search, and domain-expert copilots.

Core features

Serverless per-token inference with OpenAI/Anthropic-compatible APIs
On-demand dedicated and reserved GPU deployments
Fine-tuning and reinforcement-learning training pipelines
Large library of open LLM, vision, image and audio models
Optimized inference engine for throughput and latency

Best for

→Serving open models in production apps and agents
→Fine-tuning models on private data
→Powering code assistants, chatbots and RAG at scale

Pricing

On-Demand H100/H200
$7/GPU
On-Demand B200
$10/GPU
On-Demand B300
$12/GPU
Fine-tuning (LoRA SFT, models up to 16B): from
$0.50
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Reviews

Big-picture takes: what it's for and whether it delivers. High-engagement YouTube videos — not sponsored.

Fireworks AI: Fine-Tuning Open Source Models at Scale
The Ravit Show · 161K views
How This AI Startup Grew by 100x in Just 6 Months | Fireworks AI, Lin Qiao
EO · 81K views