--- title: "rig vs lagent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/0xplaygrounds-rig-vs-internlm-lagent" tools: ["0xplaygrounds-rig", "internlm-lagent"] --- # rig vs lagent *GraphCanon updated Sep 30, 2026* ## Verdict Pick rig if rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities; pick lagent if lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. [rig](https://rig.rs) reports 8.7k GitHub stars, 974 forks, and 102 open issues, last pushed Sep 19, 2026. [lagent](https://github.com/InternLM/lagent) has 2.3k stars, 238 forks, and 24 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [rig's repository](https://github.com/0xPlaygrounds/rig) and [lagent's repository](https://github.com/InternLM/lagent). | | [rig](/tools/0xplaygrounds-rig.md) | [lagent](/tools/internlm-lagent.md) | | --- | --- | --- | | Tagline | Build modular and scalable LLM Applications in Rust | A lightweight framework for building LLM-based agents | | Stars | 8,679 | 2,276 | | Forks | 974 | 238 | | Open issues | 102 | 24 | | Language | Rust | Python | | Adopt for | Rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities. | lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. | | Persona | - | - | | Runtime | - | - | | License | MIT | lagent is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution. | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [rig](/tools/0xplaygrounds-rig.md) | [lagent](/tools/internlm-lagent.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 12d | | Open issues (now) | 102 | 24 | | Stars delta | +351 (30d) | +8 (30d) | | Open issues delta | -11 (30d) | +1 (30d) | | Full report | [trust report](/tools/0xplaygrounds-rig/trust.md) | [trust report](/tools/internlm-lagent/trust.md) | ## Decision facts: rig - **Hosting:** self hosted - Self-hosted as a Rust library. - **Pricing:** freemium - Free to use under MIT license with potential premium support options. - **Adopt for:** Rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities. - **License detail:** MIT ## Decision facts: lagent - **Pricing:** freemium - Available freely due to its open-source nature, but customization or enterprise support might involve additional costs. - **Adopt for:** lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. - **License detail:** lagent is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution. ## Choose when ### Choose rig if… - rig is primarily Rust; lagent is Python. - License: rig is MIT, lagent is Apache-2.0. - Self-hosted as a Rust library. - Pricing: Free to use under MIT license with potential premium support options.. - Tags unique to rig: ai, artificial-intelligence, automation, generative-ai. - You should use Rig when you need to work with LLM applications in Rust and want full WASM (core library) compatibility. ### Choose lagent if… - lagent is primarily Python; rig is Rust. - License: lagent is Apache-2.0, rig is MIT. - Pricing: Available freely due to its open-source nature, but customization or enterprise support might involve additional costs.. - Tags unique to lagent: gpt, transformers. - When you need a streamlined approach to develop LLM-based agents with minimal overhead, lagent can be particularly advantageous due to its lightweight design. ## When NOT to use rig - Avoid using Rig if you are working on applications that do not require or support Rust as it is specifically built to facilitate LLM operations within a Rust environment. - Rig may not be suitable if your project cannot handle potential breaking changes, which are expected due to its rapidly evolving nature and upcoming feature updates. ## When NOT to use lagent - Avoid using lagent if your project necessitates integration with a broader set of tools that are not natively supported by this framework, as it offers limited out-of-the-box extensibility. - Steer clear if you need robust scalability features right from the start. While lightweight, lagent may require additional custom work to handle more demanding scaling requirements. ## Common questions ### What is the difference between rig and lagent? rig: Build modular and scalable LLM Applications in Rust. lagent: A lightweight framework for building LLM-based agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose rig over lagent? Choose rig over lagent when rig is primarily Rust; lagent is Python; License: rig is MIT, lagent is Apache-2.0; Self-hosted as a Rust library; Pricing: Free to use under MIT license with potential premium support options.; Tags unique to rig: ai, artificial-intelligence, automation, generative-ai; You should use Rig when you need to work with LLM applications in Rust and want full WASM (core library) compatibility. ### When should I choose lagent over rig? Choose lagent over rig when lagent is primarily Python; rig is Rust; License: lagent is Apache-2.0, rig is MIT; Pricing: Available freely due to its open-source nature, but customization or enterprise support might involve additional costs.; Tags unique to lagent: gpt, transformers; When you need a streamlined approach to develop LLM-based agents with minimal overhead, lagent can be particularly advantageous due to its lightweight design. ### When should I avoid rig? Avoid using Rig if you are working on applications that do not require or support Rust as it is specifically built to facilitate LLM operations within a Rust environment. Rig may not be suitable if your project cannot handle potential breaking changes, which are expected due to its rapidly evolving nature and upcoming feature updates. ### When should I avoid lagent? Avoid using lagent if your project necessitates integration with a broader set of tools that are not natively supported by this framework, as it offers limited out-of-the-box extensibility. Steer clear if you need robust scalability features right from the start. While lightweight, lagent may require additional custom work to handle more demanding scaling requirements. ### Is rig or lagent more popular on GitHub? rig has more GitHub stars (8,679 vs 2,276). Stars measure visibility, not whether either tool fits your constraints. ### Are rig and lagent open source? Yes - both are open-source projects on GitHub (rig: MIT, lagent: Apache-2.0). ### Where can I find alternatives to rig or lagent? GraphCanon lists graph-backed alternatives at [rig alternatives](/tools/0xplaygrounds-rig/alternatives) and [lagent alternatives](/tools/internlm-lagent/alternatives) ([rig markdown twin](/tools/0xplaygrounds-rig/alternatives.md), [lagent markdown twin](/tools/internlm-lagent/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 [this comparison](/compare/0xplaygrounds-rig-vs-internlm-lagent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, rig or lagent? rig: Very active. lagent: 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 rig and lagent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [rig trust report](/tools/0xplaygrounds-rig/trust); [lagent trust report](/tools/internlm-lagent/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=0xplaygrounds-rig`](/api/graphcanon/graph?tool=0xplaygrounds-rig) - 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/_