What Models Does Fireworks AI Support on Serverless?

Fireworks AI supports hundreds of open-source models on serverless including DeepSeek V3/V4, Qwen3, Llama 4, Kimi K2, Gemma 3, Mistral, and GPT-OSS families. It also supports vision-language models, embedding models, and text-to-speech models across multiple parameter sizes.

How Does Fireworks AI Fine-Tuning Work?

Fireworks offers supervised fine-tuning (SFT), preference fine-tuning (DPO), and reinforcement fine-tuning (RFT). You can train with LoRA or full parameter methods, use reasoning traces, and warm-start RFT from SFT checkpoints. Fine-tuned models are served at the same price as base models.

Is Fireworks AI Compatible With OpenAI SDKs?

Yes, Fireworks AI provides full OpenAI API compatibility. You can use the official OpenAI Python and Node.js SDKs by simply changing the base URL to the Fireworks endpoint. It also supports the Responses API for multi-turn conversations.

How Does Prompt Caching Reduce Costs on Fireworks AI?

Cached input tokens on Fireworks serverless are priced at 50% of standard input token rates. Using session affinity routing via the user field or x-session-affinity header improves cache hit rates, reducing costs for repeated or long-context prompts.

What GPU Options Are Available for On-Demand Deployments?

Fireworks offers H100 80GB at $7/hr, H200 141GB at $7/hr, B200 180GB at $10/hr, and B300 288GB at $12/hr for on-demand deployments. Billing is per GPU second with no extra charges for start-up times.

Fireworks AI

Name: Fireworks AI
Availability: InStock
Author: Fireworks AI, Inc.

by Fireworks AI, Inc. • Redwood City, CA, USA • Founded 2022

Fastest AI Inference Cloud for Open-Source Model Deployment

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ai inference llm deployment model fine-tuning open-source ai mlops

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2.5 /5

25 reviews

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Pricing

From $0.10/1M tokens

What is Fireworks AI?

Fireworks AI is a production-grade AI inference platform built by former Meta PyTorch engineers. It gives developers and enterprises access to hundreds of open-source LLMs, vision models, and audio models, all optimized for speed, cost, and quality. The platform supports serverless and on-demand GPU deployments, supervised fine-tuning, reinforcement learning, and model evaluation.

Fireworks processes over 10 trillion tokens per day and powers companies like Samsung, Uber, DoorDash, Shopify, and Notion. With OpenAI-compatible APIs, prompt caching, and batch inference, it enables rapid prototyping and mission-critical AI workloads at scale.

Fireworks AI — Fastest AI Inference Cloud for Open-Source Model Deployment Whether you're evaluating Fireworks AI for your team or comparing it to alternatives in the AI Code Tools category, this in-depth review covers everything: features, pricing, real user reviews, pros and cons, integrations, and direct comparisons against competitors.

Fireworks AI Demo Video

Key Features 8

Blazing-Fast Low-Latency Inference Engine for Open-Source AI Models

Fine-Tune Models With LoRA, SFT, DPO, and Reinforcement Learning

100+ Supported Models Including Text, Vision, Audio, and Embeddings

OpenAI-Compatible Drop-In API for Seamless Migration and Integration

On-Demand GPU Deployments With H100, H200, B200, and B300

Scalable Batch Inference API With 50% Cost Savings on Tokens

SOC 2, HIPAA, and GDPR Compliant Enterprise-Ready Security

Structured JSON Outputs and Function Calling for Agentic Workflows

Who Is Fireworks AI For

1 ML Engineers Building Production AI Pipelines

2 Backend Developers Integrating LLM APIs

3 AI Startups Scaling Inference Workloads

4 Enterprise Teams Deploying Custom Fine-Tuned Models

5 Data Scientists Running Model Evaluations

6 DevOps Engineers Managing GPU Infrastructure

Pros & Cons

Pros 4 benefits

Blazing Fast Inference Speeds
Extensive Open-Source Model Library
Flexible Pay-As-You-Go Pricing
Strong Enterprise Security Certifications

Cons 3 limitations

Steep Learning Curve Initially
No Free Persistent Tier
Documentation Needs More Examples

Frequently Asked Questions

5 questions

How Fireworks AI works

Fireworks AI is positioned as fastest AI Inference Cloud for Open-Source Model Deployment. Under the hood it ships 8 headline capabilities, including Blazing-Fast Low-Latency Inference Engine for Open-Source AI Models, Fine-Tune Models With LoRA, SFT, DPO, and Reinforcement Learning, 100+ Supported Models Including Text, Vision, Audio, and Embeddings, OpenAI-Compatible Drop-In API for Seamless Migration and Integration, On-Demand GPU Deployments With H100, H200, B200, and B300 and Scalable Batch Inference API With 50% Cost Savings on Tokens. Together these features cover the core workflows most teams expect from a modern ai code tools, from initial setup through day-to-day production use.

Fireworks AI runs as a self-contained product, so you can adopt it without touching the rest of your stack — useful when you want to evaluate the tool in isolation before wiring up integrations.

Who is Fireworks AI for?

Fireworks AI is most useful for ML Engineers Building Production AI Pipelines, Backend Developers Integrating LLM APIs, AI Startups Scaling Inference Workloads and Enterprise Teams Deploying Custom Fine-Tuned Models. If your team falls into one of those buckets, the feature set lines up well with how you already work — you won't be forcing a square peg into a round hole.

Beyond the obvious use case, the product tends to attract users who want a free option in the ai code tools space.

Fireworks AI pricing explained

Fireworks AI is fully free to use, with no paid tier required to access the headline functionality. That removes evaluation friction — you can sign up, run a real project through it, and decide whether it earns a permanent spot in your stack without committing budget.

Across the AI Cloudbase rubric, we score free pricing models on transparency, rate-limit honesty, and how predictable spend is at scale. Fireworks AI's free approach is unusually friendly to small teams and indie builders.

Our verdict on Fireworks AI

Fireworks AI hasn't been rated by enough reviewers yet to publish an aggregate score. The strongest signal in those reviews is that blazing fast inference speeds. The most common complaint is that steep learning curve initially — worth knowing before you commit, but rarely a deal-breaker for teams that already match the use case.

If you're evaluating Fireworks AI against alternatives, weigh it on the same 7-criteria rubric we apply to every tool: capability, integrations, pricing transparency, support, security posture, roadmap velocity, and community signal. Built by Fireworks AI, Inc., founded in 2022, the product has a clear track record you can verify before adopting it. The bottom line: Fireworks AI is a solid pick in the ai code tools category, and it deserves a spot on your shortlist if your workflow matches what it was built for.

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What's New

weekly

Video & Audio Models, AWS S3 Training Integration

Added multimodal video and audio input support for models like Qwen3 Omni and Molmo2. AWS S3 integration for secure training datasets via OIDC federation.

Feb 5

Warm-Start Training and Azure Model Uploads

Warm-start Reinforcement Fine-Tuning from SFT checkpoints. Azure Blob Storage model uploads via Azure AD federated identity authentication.

Jan 20

View all updates

User Base

10,000+ companies, 100K+ developers

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Security & Privacy

SOC 2 Type II HIPAA Compliant ISO 27001 ISO 27701 ISO 42001 GDPR Aligned CCPA Aligned

End-to-end encryption (AES-256 at rest, TLS 1.2+ in transit) Zero Data Retention for open model inference Bring Your Own Bucket (BYOB) for training data Workload isolation for dedicated deployments Audit and access logging Role-based access control (RBAC) +1 more