# Llama Stack — AI Tool Profile
> Source: https://agentrobbies.com/tools/llama-stack
> Ecosystem: META | Verified: 2026-10-11
> 100% Independent Listing • Zero Affiliate Links

## Description
Standardized API specifications and reference runtimes by Meta for building end-to-end RAG, tool calling, agentic execution loops, and synthetic data pipelines with Llama models.

## Access & Pricing
Open Source SDK & Docker distribution on GitHub.

## Key Capabilities
- Standardized agent memory, inference, and tool execution APIs
- Pluggable backends across Ollama, Together AI, Fireworks, and AWS
- Built-in evaluation, safety guardrails, and telemetry

## Alternatives & Replaces
- Fragmented bespoke agent plumbing

## Robbie's Take
**Robbie's Hardware & Practical Fit:** Excellent candidate for local execution with zero cloud lock-in. For 7B-8B parameter models, budget at least 8 GB of unified memory or VRAM (Q4_K_M quantization). For 32B-70B models, aim for 24 GB+ to maintain interactive throughput without CPU offload penalties.

## Direct Link
https://github.com/meta-llama/llama-stack