Letta vs Agno
Side-by-side comparison of two AI agent tools
Short answer
- Pick Letta for: letta is the platform for building stateful agents: AI with advanced memory that can learn and self-improve. Pick Agno for: build, run, manage agentic software at scale.
From GitHub data refreshed daily.
Lettaopen-source
Letta is the platform for building stateful agents: AI with advanced memory that can learn and self-improve over time.
Agnoopen-source
Build, run, manage agentic software at scale.
Metrics
| Letta | Agno | |
|---|---|---|
| Stars | 25.0k | 42.5k |
| Star velocity /mo | 511.2631578947368 | 560.0526315789474 |
| Commits (90d) | 7 | 351 |
| Releases (6m) | 1 | 10 |
| Overall score | 0.5606070835576371 | 0.7960554542558297 |
Pros
- +Advanced persistent memory system that allows agents to learn and improve over time across sessions
- +Dual deployment options with both local CLI tool and cloud API for different use cases and security requirements
- +Model-agnostic architecture supporting multiple LLM providers with extensive SDK support for TypeScript and Python
- +Production-ready runtime with built-in scalability, session isolation, and native tracing capabilities
- +Comprehensive monitoring and management through AgentOS UI for testing, debugging, and production oversight
- +Simple development experience - build sophisticated agents with memory and tools in approximately 20 lines of Python code
Cons
- -Requires Node.js 18+ for CLI usage, which may limit adoption in some environments
- -API-based functionality requires API keys and cloud dependency for full feature access
- -As a relatively new platform for stateful agents, may have a learning curve for developers new to persistent memory concepts
- -Python-focused platform with limited examples for other programming languages
- -Requires multiple dependencies and proper configuration of API keys and database connections
- -May have a learning curve for implementing complex multi-agent workflows and team coordination
Use Cases
- •Building coding assistants that remember project context and learn from previous debugging sessions
- •Creating customer support agents that maintain conversation history and learn customer preferences over time
- •Developing personal AI assistants that evolve their responses based on user behavior patterns and feedback
- •Building production AI agents with persistent state, memory, and custom tool integrations for customer service or automation
- •Creating multi-agent teams and workflows for complex business processes that require coordination between specialized agents
- •Enterprise deployment of AI agents with comprehensive monitoring, user session management, and production-grade reliability requirements
FAQ
- Which is more popular, Letta or Agno?
- Agno has more GitHub stars (42,524 vs 25,012).
- Which is more actively developed, Letta or Agno?
- Agno had more commits in the last 90 days (351 vs 7).
- Should I use Letta or Agno?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.