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← Back to Llama Stack Overview

Llama Stack Pricing & Plans 2026

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

Try Llama Stack Free →Compare Plans ↓

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

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

Choose Your Plan

Open-source repository

$0

mo

    Start Free Trial →
    Most Popular

    Self-hosted deployment

    $0/month Llama Stack fee + user-paid infrastructure

    mo

      Start Free Trial →

      Hosted provider usage

      $0/month Llama Stack fee + third-party usage rates

      mo

        Start Free Trial →

        Pricing sourced from Llama Stack · Last verified March 2026

        Feature Comparison

        Detailed feature comparison coming soon. Visit Llama Stack's website for complete plan details.

        View Full Features →

        Is Llama Stack Worth It?

        ✅ Why Choose Llama Stack

        • • Official Meta Llama infrastructure project with a public GitHub repository and inspectable source code.
        • • Standardized APIs help teams build against common interfaces for inference, agents, tools, safety, RAG, and evaluation.
        • • Provider-based distribution model supports local development and production-oriented hosted deployments.
        • • Documented CLI, Python package installation, client SDKs, and container workflows make it practical for developer-led adoption.
        • • Supports a broad ecosystem of inference providers, vector databases, safety tools, and deployment targets through pluggable providers.
        • • Useful for teams that want portability across local, cloud, and on-device Llama application environments.

        ⚠️ Consider This

        • • It is developer infrastructure, not a turnkey no-code agent platform.
        • • No fixed hosted SaaS pricing tiers are listed for the open-source repository.
        • • Total cost can vary significantly depending on model hosting, GPU requirements, cloud infrastructure, and third-party provider usage.
        • • Production use requires technical evaluation of distributions, providers, deployment requirements, security posture, and operational maturity.
        • • Some capabilities depend on selected providers, so teams must verify whether their required inference, RAG, safety, evaluation, or post-training workflow is supported by the distribution they plan to use.

        What Users Say About Llama Stack

        👍 What Users Love

        • ✓Official Meta Llama infrastructure project with a public GitHub repository and inspectable source code.
        • ✓Standardized APIs help teams build against common interfaces for inference, agents, tools, safety, RAG, and evaluation.
        • ✓Provider-based distribution model supports local development and production-oriented hosted deployments.
        • ✓Documented CLI, Python package installation, client SDKs, and container workflows make it practical for developer-led adoption.
        • ✓Supports a broad ecosystem of inference providers, vector databases, safety tools, and deployment targets through pluggable providers.
        • ✓Useful for teams that want portability across local, cloud, and on-device Llama application environments.

        👎 Common Concerns

        • ⚠It is developer infrastructure, not a turnkey no-code agent platform.
        • ⚠No fixed hosted SaaS pricing tiers are listed for the open-source repository.
        • ⚠Total cost can vary significantly depending on model hosting, GPU requirements, cloud infrastructure, and third-party provider usage.
        • ⚠Production use requires technical evaluation of distributions, providers, deployment requirements, security posture, and operational maturity.
        • ⚠Some capabilities depend on selected providers, so teams must verify whether their required inference, RAG, safety, evaluation, or post-training workflow is supported by the distribution they plan to use.

        Pricing FAQ

        Is this the official Llama Stack project?

        Yes. The listed URL is https://github.com/meta-llama/llama-stack, the official public GitHub repository for Llama Stack. This revised listing is based on the Llama Stack identity rather than unrelated Open GenAI Stack repository data.

        What does Llama Stack provide?

        Llama Stack provides standardized APIs and composable building blocks for Llama application development, including inference, agents, tools, safety, retrieval, evaluation, and provider-based distributions. It is intended for developers building AI applications that need consistent behavior across local, hosted, and production environments.

        Is pricing available for this tool?

        Yes. The public repository has a $0 listed software price, self-hosted use has a $0/month Llama Stack fee, and no fixed SaaS subscription tiers are listed in the repository. Deployment costs may still apply for compute, GPUs, hosting, model providers, vector databases, storage, observability, and engineering operations.

        Who is this tool best suited for?

        Llama Stack is best suited for developers, AI engineers, and platform teams that want standardized infrastructure for building Llama-based AI applications and agents. It is less appropriate for business users who need a finished no-code product with packaged onboarding, billing, and support.

        How should teams evaluate it against other AI agent builders?

        Teams should evaluate Llama Stack as an open-source framework and API layer rather than a hosted agent workspace. Compare its provider matrix, distribution model, SDK support, documentation, license terms, deployment requirements, and operational complexity against alternatives such as LangChain, Ollama, Together AI, and OpenAI Agents SDK.

        Ready to Get Started?

        AI builders and operators use Llama Stack to streamline their workflow.

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        More about Llama Stack

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