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← Back to Fireworks AI Overview

Fireworks AI Pricing & Plans 2026

Complete pricing guide for Fireworks AI. Compare all plans, analyze costs, and find the perfect tier for your needs.

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Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Fireworks AI is worth it →

🆓Free Tier Available
💎3 Paid Plans
⚡No Setup Fees

Choose Your Plan

Serverless

Per-million-token pricing per model (text models from ~$0.20/M up depending on size; image models per-image)

usage

    Start Free Trial →
    Most Popular

    On-Demand Dedicated

    Per-GPU-hour for pinned deployments

    hourly

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      Enterprise

      Custom

      contract

        Contact Sales →

        Pricing sourced from Fireworks AI · Last verified March 2026

        Feature Comparison

        Detailed feature comparison coming soon. Visit Fireworks AI's website for complete plan details.

        View Full Features →

        Is Fireworks AI Worth It?

        ✅ Why Choose Fireworks AI

        • • Reliable function calling, JSON mode, and parallel tool calls across the open-model catalog — table stakes for production agents
        • • FireFunction-V2 is purpose-built for tool-calling accuracy, materially beating generic Llama tool-use in agentic loops
        • • Three pricing tiers (serverless / dedicated GPU-hour / Enterprise) cover prototype-to-scale without rehosting

        ⚠️ Consider This

        • • Latency is good but typically not as low as Groq's LPU-based inference
        • • Per-token pricing is competitive but not always the cheapest — DeepSeek's official API or OpenRouter aggregation can undercut on specific models
        • • Serverless rate limits can surprise high-burst workloads and force an earlier-than-expected jump to dedicated deployments

        What Users Say About Fireworks AI

        👍 What Users Love

        • ✓Reliable function calling, JSON mode, and parallel tool calls across the open-model catalog — table stakes for production agents
        • ✓FireFunction-V2 is purpose-built for tool-calling accuracy, materially beating generic Llama tool-use in agentic loops
        • ✓Three pricing tiers (serverless / dedicated GPU-hour / Enterprise) cover prototype-to-scale without rehosting

        👎 Common Concerns

        • ⚠Latency is good but typically not as low as Groq's LPU-based inference
        • ⚠Per-token pricing is competitive but not always the cheapest — DeepSeek's official API or OpenRouter aggregation can undercut on specific models
        • ⚠Serverless rate limits can surprise high-burst workloads and force an earlier-than-expected jump to dedicated deployments

        Pricing FAQ

        What models are available on Fireworks AI?

        Fireworks provides access to a wide catalog of popular open-source models including Llama 3.1 (8B, 70B, and 405B), Llama 3.3 70B, DeepSeek V3, Qwen 2.5 (7B, 32B, and 72B), Gemma 2 (9B and 27B), Mixtral 8x22B, Mistral variants, and multimodal models like Llama 3.2 Vision. The library includes over 50 serverless models spanning LLMs, vision models, and image generation models like SDXL, with new models added frequently and often on launch day.

        How does Fireworks AI pricing work?

        Fireworks uses per-token pricing that varies by model size and capability. Smaller models like Llama 3.1 8B are available at lower per-token rates, while larger models like Llama 3.1 405B cost more per token. A free tier is available for experimentation. Serverless endpoints require no upfront cost or GPU provisioning fees. On-demand dedicated GPU deployments are available for production workloads requiring guaranteed capacity. Enterprise customers can negotiate volume discounts with committed spend agreements.

        Is Fireworks AI suitable for enterprise use?

        Yes. Fireworks is SOC2, HIPAA, and GDPR compliant, offers zero data retention policies, and supports bring-your-own-cloud deployments for complete data sovereignty. Enterprise customers include Notion, Sourcegraph, Cursor, and Quora. The platform provides dedicated support, SLAs, and globally distributed infrastructure for mission-critical workloads.

        Can I fine-tune models on Fireworks AI?

        Yes. Fireworks offers fine-tuning with advanced techniques including reinforcement learning, quantization-aware tuning, and adaptive speculation. You can customize any supported open-source model for your specific use case and deploy the tuned model directly on the Fireworks inference cloud without managing separate training and serving infrastructure.

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        More about Fireworks AI

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