Agno vs Strands: Agent Frameworks Comparison
Compare Agno and Strands side by side. Both are tools in the Agent Frameworks category.
Updated April 29, 2026
The short answer
Choose Agno if production-first design with stateless scaling and AgentOS runtime.
Choose Strands if production-proven by AWS teams (Amazon Q, AWS Glue).
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Quick Comparison
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|---|---|---|
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | Free open-source | — |
| Best For | Python teams building production AI agents that want first-class deployment, observability, and multi-agent support | — |
| Website | agno.com | github.com |
| Key Features |
| — |
| Use Cases |
| — |
Pros & Cons: Agno vs Strands
- +Production-first design with stateless scaling and AgentOS runtime
- +39K+ GitHub stars and 424 active contributors
- +100+ pre-built tools including MCP support
- +Control plane UI is rare in OSS agent frameworks
- +Memory in your DB — no vendor lock-in
- −Newer than LangChain ecosystem — fewer third-party integrations
- −Python-only — no JS/TS SDK
- −Smaller community than LangChain at production scale
- −Less battle-tested at Fortune 500 scale than LangGraph
- +Production-proven by AWS teams (Amazon Q, AWS Glue)
- +True provider-agnostic support for 8+ LLM providers
- +Comprehensive multi-agent orchestration with A2A protocol
- +Rich AWS ecosystem integration
- +Open-source with active development
- −Relatively new framework (launched 2025)
- −AWS ecosystem bias in design and tooling
- −Variable costs depending on chosen providers
Pricing: Agno vs Strands
- · Full Python SDK + AgentOS runtime
- · Control plane UI included
- · 100+ tool integrations + MCP
- · Apache 2.0 license
- · Full SDK access
- · Multi-agent orchestration
- · Multi-modal support
- · Provider-agnostic
- · Pay for model usage
- · AWS infrastructure
- · Production scalability
- · Enterprise support
- · OpenAI pricing
- · Anthropic pricing
- · Gemini pricing
- · Custom model pricing
What people are saying
Curated quotes from Hacker News, Reddit, Product Hunt, and review blogs. Dates shown so you can judge whether early criticism still applies.
- +
“Agno has emerged as one of the fastest-growing AI agent frameworks in 2026 — 39,100+ stars and a 424-contributor community.”
— DecisionCrafters review, DecisionCrafters · Apr 2026 - +
“Purpose-built for production with stateless scaling, session management, and enterprise features — closer to a 'framework + runtime + control plane' than just an SDK.”
— WorkOS engineering blog, WorkOS Blog · Mar 2026 - +
“Memory is stored in your database — you own the data, not the vendor. That alone made it the right call for our compliance posture.”
— Production team review, DecisionCrafters · Mar 2026 - ·
“Smaller community than LangChain at production scale — but the documentation gap is closing fast.”
— Framework comparison, AI Agents Directory · Mar 2026
When to Choose Agno vs Strands
- Production multi-agent systems with stateless scaling
- Customer-facing AI assistants with session management
- Internal-tool agents with monitoring dashboards
How to Choose a Agent Frameworks Tool
Key criteria to evaluate when comparing Agent Frameworks solutions:
About Agno
Agno (formerly Phidata) is an open-source Python framework for building production-grade AI agents and multi-agent systems. With 39,100+ GitHub stars and an active 424-contributor community, it's emerged as one of the fastest-growing agent frameworks in 2026.
Agno provides three integrated layers: a Python SDK for building individual agents and multi-agent teams, a stateless FastAPI runtime called AgentOS for production deployment, and a control plane UI for monitoring, session management, and team operations. It supports 23+ LLM providers (OpenAI, Anthropic Claude, Google Gemini, and more) and ships 100+ pre-built tool integrations including web search, data analysis, file operations, and Model Context Protocol (MCP) servers.
Memory and knowledge systems are first-class: user memories, session memories, and RAG knowledge bases are stored in your database — you own the data, not Agno. Recent v2.5.13 (March 2026) added ReliabilityEval for agent evaluation, enhanced AgentOS APIs for session management, and Slack interface improvements. Agno is positioned as the production-first alternative to LangChain/LangGraph for Python teams.
About Strands
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.
What is Agent Frameworks?
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworkstools →Frequently Asked Questions
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