--- title: "judgeval vs anything-llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/judgmentlabs-judgeval-vs-mintplex-labs-anything-llm" tools: ["judgmentlabs-judgeval", "mintplex-labs-anything-llm"] --- # judgeval vs anything-llm *GraphCanon updated Jul 12, 2026* ## Verdict Pick judgeval if judgeval is a Python tool that aids in the continuous improvement of AI agents through comprehensive environment data and evaluations, supporting methodologies like reinforcement learning and prompt engineering; pick anything-llm if self-hosted AI agent experience with robust deployment scripts across multiple environments. [judgeval](https://judgmentlabs.ai/) reports 1.0k GitHub stars, 93 forks, and 18 open issues, last pushed Jul 7, 2026. [anything-llm](https://anythingllm.com) has 63k stars, 6.9k forks, and 320 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [judgeval's repository](https://github.com/JudgmentLabs/judgeval) and [anything-llm's repository](https://github.com/Mintplex-Labs/anything-llm). | | [judgeval](/tools/judgmentlabs-judgeval.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Tagline | The Continuous-Improvement Stack for Agents | Self-hosted agent experience with deployment scripts for multiple environments | | Stars | 1,040 | 63,100 | | Forks | 93 | 6,907 | | Open issues | 18 | 320 | | Language | Python | JavaScript | | Adopt for | Judgeval is a Python tool that aids in the continuous improvement of AI agents through comprehensive environment data and evaluations, supporting methodologies like reinforcement learning and prompt engineering. | Self-hosted AI agent experience with robust deployment scripts across multiple environments. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [judgeval](/tools/judgmentlabs-judgeval.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Days since push | 3d | 0d | | Open issues (now) | 18 | 320 | | Full report | [trust report](/tools/judgmentlabs-judgeval/trust.md) | [trust report](/tools/mintplex-labs-anything-llm/trust.md) | ## Decision facts: judgeval - **Adopt for:** Judgeval is a Python tool that aids in the continuous improvement of AI agents through comprehensive environment data and evaluations, supporting methodologies like reinforcement learning and prompt engineering. ## Decision facts: anything-llm - **Adopt for:** Self-hosted AI agent experience with robust deployment scripts across multiple environments. ## Choose when ### Choose judgeval if… - judgeval is primarily Python; anything-llm is JavaScript. - License: judgeval is Apache-2.0, anything-llm is MIT. - Tags unique to judgeval: agent, agents, grpo, langchain. - Also covers Evaluation & Observability. - You are working on an AI project where continuous monitoring and enhancement of your agent's performance are critical. ### Choose anything-llm if… - anything-llm is primarily JavaScript; judgeval is Python. - License: anything-llm is MIT, judgeval is Apache-2.0. - Tags unique to anything-llm: agent-computer, agent-harness, llm, local-ai. - Also covers Inference & Serving. - When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more. ## When NOT to use judgeval - If you are looking for a tool focused solely on the theoretical aspects of AI development without practical, continuous improvement methodologies. - You require a solution that only supports evaluation metrics and does not offer integrated environment data support, diverging from Judgeval’s comprehensive approach. ## When NOT to use anything-llm - Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. - Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods. ## Common questions ### What is the difference between judgeval and anything-llm? judgeval: The Continuous-Improvement Stack for Agents. anything-llm: Self-hosted agent experience with deployment scripts for multiple environments. See the comparison table for live GitHub stats and shared categories. ### When should I choose judgeval over anything-llm? Choose judgeval over anything-llm when judgeval is primarily Python; anything-llm is JavaScript; License: judgeval is Apache-2.0, anything-llm is MIT; Tags unique to judgeval: agent, agents, grpo, langchain; Also covers Evaluation & Observability; You are working on an AI project where continuous monitoring and enhancement of your agent's performance are critical. ### When should I choose anything-llm over judgeval? Choose anything-llm over judgeval when anything-llm is primarily JavaScript; judgeval is Python; License: anything-llm is MIT, judgeval is Apache-2.0; Tags unique to anything-llm: agent-computer, agent-harness, llm, local-ai; Also covers Inference & Serving; When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more. ### When should I avoid judgeval? If you are looking for a tool focused solely on the theoretical aspects of AI development without practical, continuous improvement methodologies. You require a solution that only supports evaluation metrics and does not offer integrated environment data support, diverging from Judgeval’s comprehensive approach. ### When should I avoid anything-llm? Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods. ### Is judgeval or anything-llm more popular on GitHub? anything-llm has more GitHub stars (63,100 vs 1,040). Stars measure visibility, not whether either tool fits your constraints. ### Are judgeval and anything-llm open source? Yes - both are open-source projects on GitHub (judgeval: Apache-2.0, anything-llm: MIT). ### Where can I find alternatives to judgeval or anything-llm? GraphCanon lists graph-backed alternatives at [judgeval alternatives](/tools/judgmentlabs-judgeval/alternatives) and [anything-llm alternatives](/tools/mintplex-labs-anything-llm/alternatives) ([judgeval markdown twin](/tools/judgmentlabs-judgeval/alternatives.md), [anything-llm markdown twin](/tools/mintplex-labs-anything-llm/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/judgmentlabs-judgeval-vs-mintplex-labs-anything-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, judgeval or anything-llm? judgeval: Very active. anything-llm: 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 judgeval and anything-llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [judgeval trust report](/tools/judgmentlabs-judgeval/trust); [anything-llm trust report](/tools/mintplex-labs-anything-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=judgmentlabs-judgeval`](/api/graphcanon/graph?tool=judgmentlabs-judgeval) - 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/_