What is Fireworks AI used for?

Fireworks AI is an inference and training platform for serving and customizing open models at low latency, with options from guided fine-tuning to custom reinforcement learning. It is a good fit for serving open models for a production app, training a specialized model on proprietary data and reducing spend on closed-model API calls.

How much does Fireworks AI cost?

Fireworks AI is a paid product with no free plan. Usage-based. Embeddings start at $0.008 per million input tokens, managed training at $0.50 per million tokens, and on-demand GPUs at $8.00 per hour for an H100. Serverless inference is priced per token.

Is Fireworks AI open source?

No. Fireworks AI is proprietary (closed-source) software and can't be self-hosted. Open-source alternatives to Fireworks AI include vLLM, LocalAI and SGLang.

What are some alternatives to Fireworks AI?

Fireworks AI competes with Together AI, DeepInfra and Baseten. For open-source options, see Enlisted's ranked list of open-source Fireworks AI alternatives.

Fireworks AI: features, pricing and alternatives

About Fireworks AI

Fireworks AI is a platform for running generative AI models and adapting them to specific tasks. It focuses on open models: customers can serve current open-source models through hosted inference, or train their own versions and deploy them on the same infrastructure.

Training is offered at several levels of control. A guided path lets a user describe a task, review the plan and cost and approve a run, a configuration-led option handles scheduling and the production handoff, and a lower-level option lets teams write their own loss, trainer and reinforcement learning loop. Fireworks Nexus is presented as a drop-in replacement for closed-model APIs that routes each task to a suitable open or closed model.

Fireworks is a proprietary hosted service with a published pricing page, plus demos and sales contact for larger teams. It is aimed at companies building AI products, including coding tools, that want control over their model rather than relying only on closed vendors.

Key features

Hosted inference for open models
Guided, configuration-led and custom training
Reinforcement learning on the vendor's GPUs
Fast deployment of trained checkpoints
Model routing across open and closed models

Good fit for

→Serving open models for a production app
→Training a specialized model on proprietary data
→Reducing spend on closed-model API calls

Tags: ai-inference; fine-tuning; open-models; llm-api; reinforcement-learning; model-training; model-routing; mlops

Fireworks AI: questions and answers

What is Fireworks AI used for?: Fireworks AI is an inference and training platform for serving and customizing open models at low latency, with options from guided fine-tuning to custom reinforcement learning. It is a good fit for serving open models for a production app, training a specialized model on proprietary data and reducing spend on closed-model API calls.
How much does Fireworks AI cost?: Fireworks AI is a paid product with no free plan. Usage-based. Embeddings start at $0.008 per million input tokens, managed training at $0.50 per million tokens, and on-demand GPUs at $8.00 per hour for an H100. Serverless inference is priced per token.
Is Fireworks AI open source?: No. Fireworks AI is proprietary (closed-source) software and can't be self-hosted. Open-source alternatives to Fireworks AI include vLLM, LocalAI and SGLang.
What are some alternatives to Fireworks AI?: Fireworks AI competes with Together AI, DeepInfra and Baseten. For open-source options, see Enlisted's ranked list of open-source Fireworks AI alternatives.