Fireworks AI
Fireworks AI / fireworks.ai
High-performance LLM inference API focused on speed and cost efficiency for open source model deployment at production scale, with function calling, JSON mode, and vision model support.
Pricing
Free
Free plan
Yes
Category
Developer Tools
Platforms
2
Free plan
Yes
API access
Yes
Open source
No
Platforms
2
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What is Fireworks AI?
Fireworks AI is an LLM inference API provider focused on fast, cost-efficient inference for open source models at production scale, founded by former Google engineers. Supports Llama 3, Mistral, Mixtral, Code Llama, Phi, Gemma, and others through a consistent OpenAI-compatible API. Function calling and JSON mode bring structured output control to open source models. At $0.10/M tokens for smaller models, Fireworks pricing is competitive with Together AI and Groq. Most compelling for developers who want fast open source model inference through a reliable API without the infrastructure complexity of self-hosting.
How Fireworks AI works
Fireworks AI runs as ml inference platform software built around text and code workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on web and api, with API access for teams that want to embed it into their own products.
Watch Fireworks AI in action
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What makes it worth shortlisting
The capabilities that matter most for teams evaluating Fireworks AI.
Fast inference
Optimised infrastructure delivering low-latency open source model inference.
OpenAI-compatible API
Uses OpenAI API format enabling migration from OpenAI with minimal code changes.
Function calling
Structured function calling support for open source models enabling tool use and structured output.
Best use cases
Who should use it
Pros
- Fast inference speeds competitive with Groq for open source model deployment
- OpenAI-compatible API enables easy migration from OpenAI
- Competitive pricing at $0.10/M tokens for smaller models
- Function calling and JSON mode bring structured output to open source models
Cons
- Model selection less comprehensive than Hugging Face for niche models
- Dedicated deployment requires custom pricing engagement
- Less community ecosystem than Together AI or Groq at this stage
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Is it worth the price?
Free $1 in monthly credits. Serverless API from $0.10/M tokens for small models. Dedicated deployment custom.
Model
Usage-based
Starting price
Free
Free trial
No
Tools like Fireworks AI
Groq is the fastest inference provider for supported models. Together AI has a broader model library. Replicate provides more niche model coverage. Cloudflare Workers AI provides edge inference.
Fireworks AI vs Replicate
A side-by-side look at the closest alternative in this category.
Fireworks AI
Fireworks AI
Replicate
Replicate
Free $1 in monthly credits. Serverless API from $0.10/M tokens for small models. Dedicated deployment custom.
Free tier with limited compute credits. Usage-based pricing per model run, starting from fractions of a cent for small models to several cents for large GPU-intensive models. Enterprise custom pricing.
SOC 2 Type II. GDPR compliant. Enterprise includes data handling agreements.
Enterprise custom pricing includes SLAs, dedicated infrastructure, and security controls.
Review Fireworks AI data handling policy. Inference requests processed on Fireworks infrastructure.
Review individual model licences before commercial deployment. Some open source models have non-commercial or restricted use licences. Replicate does not own the models it hosts.
- Fast inference speeds competitive with Groq for open source model deployment
- OpenAI-compatible API enables easy migration from OpenAI
- Competitive pricing at $0.10/M tokens for smaller models
- Function calling and JSON mode bring structured output to open source models
- Run thousands of open source models without GPU infrastructure management
- Usage-based pricing is cost-effective for variable workloads
- Clean developer experience with good documentation
- Fast prototyping across diverse model types
- Model selection less comprehensive than Hugging Face for niche models
- Dedicated deployment requires custom pricing engagement
- Less community ecosystem than Together AI or Groq at this stage
- Developer-only platform with limited accessibility for non-technical users
- Pricing per model run can add up for high-volume production use
- Not all models are maintained or up to date
- Large-scale production workloads may be cheaper with managed GPU infrastructure
Technical & deployment info
Key facts about model providers, platforms, and team support.
Model Provider
Meta, Mistral AI, Microsoft, Google, Open Source
Models
Llama 3, Mistral, Mixtral, Phi, Gemma, Code Llama
Platforms
Web, API
Deployment
SaaS, API
Integrations
Python SDK, JavaScript SDK, OpenAI-compatible, REST API
Team Collaboration
No
Launch Year
2022
Security & privacy
Compliance signals and data-handling notes as reported by the vendor.
SOC 2 Type II. GDPR compliant. Enterprise includes data handling agreements.
Review Fireworks AI data handling policy. Inference requests processed on Fireworks infrastructure.
What users are saying
Verified reviews from signed-in users, stored in the backend and averaged into this tool's rating.
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Common questions about Fireworks AI
Editorial Verdict
Should you use Fireworks AI?
Fireworks AI is a strong choice for developers who need fast, cost-efficient inference for open source models through a reliable OpenAI-compatible API.
Last verified July 24, 2026.