Llama Stack vs Strands: Agent Frameworks Comparison

Llama Stack is Meta open-source framework that defines and standardizes core building blocks for AI application development, providing a unified set of APIs with implementations from leading service providers. Launched to simplify deployment across different providers, Llama Stack collaborates with partners including NVIDIA NeMo microservices, IBM, Red Hat, and Dell Technologies. The framework is completely free and open-source under Meta permissive licensing, with costs only for API usage when using hosted Llama models through cloud providers. Pricing varies by model and provider: Llama 3.1 8B Instruct starts at USD 0.020/USD 0.050 per million tokens (input/output), Llama 4 Scout at USD 0.0800 per million tokens, and Llama 4 Maverick at USD 0.150/USD 0.600 per million tokens. Recent pricing reductions include 50 percent cuts for Llama 3.1 405B and Llama 3.3 70B models. While the project shows robust community activity and regular engagement calls, developers report challenges including setup and configuration complexity, build failures, import errors suggesting documentation gaps, Windows compatibility issues, and lack of security policies.

Strands Agents is an open-source AI agent SDK developed by AWS that takes a model-driven approach to building and running AI agents in just a few lines of code. Launched as a preview in May 2025, Strands reached version 1.0 in July 2025, bringing production-ready multi-agent orchestration capabilities. The framework uses the reasoning abilities of modern LLMs to handle planning and tool usage autonomously, eliminating the need for hardcoding complex task flows.

Strands is actively used in production by multiple AWS teams, including Kiro, Amazon Q Developer, and AWS Glue. The SDK supports multiple AI providers including Amazon Bedrock, Anthropic, Gemini, LiteLLM, Llama, Ollama, OpenAI, and Writer, making it truly provider-agnostic. Strands 1.0 introduced new primitives for multi-agent architectures, support for the Agent-to-Agent (A2A) protocol, a session manager for retrieving agent state from remote datastores, and improved async support throughout the SDK.

The framework offers comprehensive features including multi-modal support (text, speech, and image processing), rich AWS service integrations, extensibility for custom tools, and robust observability capabilities. With natural language workflow definitions through Agent SOPs and integration with Model Context Protocol (MCP), Strands provides a modern, scalable approach to building production-grade AI agents.