--- title: "letta vs honcho" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/letta-ai-letta-vs-plastic-labs-honcho" tools: ["letta-ai-letta", "plastic-labs-honcho"] --- # letta vs honcho Neutral, constraint-first comparison with live GitHub stats. | | [letta](/tools/letta-ai-letta.md) | [honcho](/tools/plastic-labs-honcho.md) | | --- | --- | --- | | Tagline | Platform for stateful agents with advanced memory capabilities | Memory library for building stateful agents | | Stars | 23,708 | 5,846 | | Forks | 2,510 | 698 | | Open issues | 49 | 155 | | Language | Python | Python | | Adopt for | Letta is a platform for building AI agents with advanced memory capabilities, supporting both local and cloud deployment, making it ideal for projects that require persistent learning and state management. | Honcho provides memory infrastructure for building stateful AI agents capable of dynamically understanding entities over time through message storage, event tracking, reasoning, and insight queries. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | LLM Frameworks, AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [letta](/tools/letta-ai-letta.md) | [honcho](/tools/plastic-labs-honcho.md) | | --- | --- | --- | | Days since push | 4d | 0d | | Open issues (now) | 49 | 155 | | Security scan | 8 low (8 low) | No lockfile | | Full report | [trust report](/tools/letta-ai-letta/trust.md) | [trust report](/tools/plastic-labs-honcho/trust.md) | **Typed relationship:** letta _(alternative)_ honcho Letta and honcho both offer tools or libraries to build stateful agents with advanced memory capabilities. ## Shared compatibility - **Python**: [letta](/tools/letta-ai-letta.md) - Python runtime; [honcho](/tools/plastic-labs-honcho.md) - Python runtime ## Decision facts: letta - **Pricing:** unknown - Details regarding pricing are not provided in the repository data. - **Requirements:** Installation requires Node.js version 22.19+; Dependencies include the Letta Code CLI tool installed globally via npm. - **Adopt for:** Letta is a platform for building AI agents with advanced memory capabilities, supporting both local and cloud deployment, making it ideal for projects that require persistent learning and state management. ## Decision facts: honcho - **Adopt for:** Honcho provides memory infrastructure for building stateful AI agents capable of dynamically understanding entities over time through message storage, event tracking, reasoning, and insight queries. ## Choose when ### Choose letta if… - License: letta is Apache-2.0, honcho is AGPL-3.0. - Pricing: Details regarding pricing are not provided in the repository data.. - Requirements: Installation requires Node.js version 22.19+; Dependencies include the Letta Code CLI tool installed globally via npm.. - Letta and honcho both offer tools or libraries to build stateful agents with advanced memory capabilities. - Tags unique to letta: self-improvement, memory-system, development-platform, cli-tool. - Also covers LLM Frameworks. - Use Letta when you need a platform to develop AI agents that can learn and self-improve over time through their interactions. ### Choose honcho if… - License: honcho is AGPL-3.0, letta is Apache-2.0. - Letta and honcho both offer tools or libraries to build stateful agents with advanced memory capabilities. - Tags unique to honcho: embeddings, continual-learning, long-term-memory, context-engineering. - - When you need a system that can store messages and events to maintain long-term agent context. ## When NOT to use letta - Avoid using Letta if your project strictly needs real-time data processing without statefulness; it focuses on agents with memory capabilities which adds to the complexity. - Do not use Letta if you are looking for a minimalistic solution since its advanced features and SDK might introduce unnecessary overhead. ## When NOT to use honcho - - If your application does not require stateful memory and dynamic tracking of entities over time. - - When the project does not align with Honcho's model of peer-centric reasoning and multi-peer perspective which might be unnecessary for straightforward agent needs. ## Common questions ### What is the difference between letta and honcho? letta: Platform for stateful agents with advanced memory capabilities. honcho: Memory library for building stateful agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose letta over honcho? Choose letta over honcho when License: letta is Apache-2.0, honcho is AGPL-3.0; Pricing: Details regarding pricing are not provided in the repository data.; Requirements: Installation requires Node.js version 22.19+; Dependencies include the Letta Code CLI tool installed globally via npm.; Letta and honcho both offer tools or libraries to build stateful agents with advanced memory capabilities; Tags unique to letta: self-improvement, memory-system, development-platform, cli-tool; Also covers LLM Frameworks; Use Letta when you need a platform to develop AI agents that can learn and self-improve over time through their interactions. ### When should I choose honcho over letta? Choose honcho over letta when License: honcho is AGPL-3.0, letta is Apache-2.0; Letta and honcho both offer tools or libraries to build stateful agents with advanced memory capabilities; Tags unique to honcho: embeddings, continual-learning, long-term-memory, context-engineering; - When you need a system that can store messages and events to maintain long-term agent context. ### When should I avoid letta? Avoid using Letta if your project strictly needs real-time data processing without statefulness; it focuses on agents with memory capabilities which adds to the complexity. Do not use Letta if you are looking for a minimalistic solution since its advanced features and SDK might introduce unnecessary overhead. ### When should I avoid honcho? - If your application does not require stateful memory and dynamic tracking of entities over time. - When the project does not align with Honcho's model of peer-centric reasoning and multi-peer perspective which might be unnecessary for straightforward agent needs. ### Is letta or honcho more popular on GitHub? letta has more GitHub stars (23,708 vs 5,846). Stars measure visibility, not whether either tool fits your constraints. ### Are letta and honcho open source? Yes - both are open-source projects on GitHub (letta: Apache-2.0, honcho: AGPL-3.0). ### Where can I find alternatives to letta or honcho? GraphCanon lists graph-backed alternatives at /tools/letta-ai-letta/alternatives and /tools/plastic-labs-honcho/alternatives (/tools/letta-ai-letta/alternatives.md, /tools/plastic-labs-honcho/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/letta-ai-letta-vs-plastic-labs-honcho.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, letta or honcho? letta: Very active. honcho: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for letta and honcho? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: letta: /tools/letta-ai-letta/trust; honcho: /tools/plastic-labs-honcho/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=letta-ai-letta`](/api/graphcanon/graph?tool=letta-ai-letta) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_