--- title: "evalplus vs LLMDebugger" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evalplus-evalplus-vs-floridsleeves-llmdebugger" tools: ["evalplus-evalplus", "floridsleeves-llmdebugger"] --- # evalplus vs LLMDebugger *GraphCanon updated Aug 5, 2026* ## Verdict Pick evalplus if evalplus offers tools for rigorously benchmarking and evaluating large language models like GPT-4 and ChatGPT in synthesizing program code using Python under the Apache-2.0 license; pick LLMDebugger if lLMDebugger offers step-by-step verification of runtime execution for large language models. [evalplus](https://evalplus.github.io) reports 1.8k GitHub stars, 205 forks, and 71 open issues, last pushed Oct 2, 2025. [LLMDebugger](https://github.com/FloridSleeves/LLMDebugger) has 587 stars, 56 forks, and 5 open issues, last pushed Sep 10, 2024. Figures are from public GitHub metadata via [evalplus's repository](https://github.com/evalplus/evalplus) and [LLMDebugger's repository](https://github.com/FloridSleeves/LLMDebugger). | | [evalplus](/tools/evalplus-evalplus.md) | [LLMDebugger](/tools/floridsleeves-llmdebugger.md) | | --- | --- | --- | | Tagline | Rigorous evaluation of LLM-synthesized code | A Large Language Model Debugger verifying runtime execution step by step | | Stars | 1,794 | 587 | | Forks | 205 | 56 | | Open issues | 71 | 5 | | Language | Python | Python | | Adopt for | evalplus offers tools for rigorously benchmarking and evaluating large language models like GPT-4 and ChatGPT in synthesizing program code using Python under the Apache-2.0 license. | LLMDebugger offers step-by-step verification of runtime execution for large language models. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The LLMDebugger is distributed under the Apache-2.0 license. | | Categories | Evaluation & Observability | Developer Tools, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [evalplus](/tools/evalplus-evalplus.md) | [LLMDebugger](/tools/floridsleeves-llmdebugger.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 306d | 693d | | Open issues (now) | 71 | 5 | | Owner type | Organization | User | | Full report | [trust report](/tools/evalplus-evalplus/trust.md) | [trust report](/tools/floridsleeves-llmdebugger/trust.md) | ## Shared compatibility - **Python**: [evalplus](/tools/evalplus-evalplus.md) - Python runtime; [LLMDebugger](/tools/floridsleeves-llmdebugger.md) - Python runtime ## Decision facts: evalplus - **Adopt for:** evalplus offers tools for rigorously benchmarking and evaluating large language models like GPT-4 and ChatGPT in synthesizing program code using Python under the Apache-2.0 license. ## Decision facts: LLMDebugger - **Pricing:** freemium - Free for use, based on its open-source nature with an Apache-2.0 license. - **Adopt for:** LLMDebugger offers step-by-step verification of runtime execution for large language models. - **License detail:** The LLMDebugger is distributed under the Apache-2.0 license. ## Choose when ### Choose evalplus if… - Tags unique to evalplus: benchmark, chatgpt, efficiency, program-synthesis. - evalplus ships Docker support for self-hosted deployment. - When you need advanced benchmarks specific to large language model generated program synthesis, such as from GPT-4 or ChatGPT. ### Choose LLMDebugger if… - Pricing: Free for use, based on its open-source nature with an Apache-2.0 license.. - Tags unique to LLMDebugger: acl'24, llm debugging, python debugger for ai, runtime verification. - Also covers Developer Tools. - When detailed step-by-step inspection of the runtime behavior of large language models is required, LLMDebugger can provide precise insights into each execution phase. ## When NOT to use evalplus - Avoid if you require broad language model benchmarking that is not specifically focused on program synthesis capabilities. - Do not use evalplus if your project does not benefit from or need Docker-based isolation for code execution safety measures, such as in controlled lab environments without external dependencies. ## When NOT to use LLMDebugger - Avoid using if you are only interested in higher-level performance metrics rather than the intricate details of runtime behavior, as LLMDebugger emphasizes step-by-step execution. - Not recommended for teams lacking experience with Python or specific to this tool's installation and usage workflow that involves setting up a Conda environment. ## Common questions ### What is the difference between evalplus and LLMDebugger? evalplus: Rigorous evaluation of LLM-synthesized code. LLMDebugger: A Large Language Model Debugger verifying runtime execution step by step. See the comparison table for live GitHub stats and shared categories. ### When should I choose evalplus over LLMDebugger? Choose evalplus over LLMDebugger when Tags unique to evalplus: benchmark, chatgpt, efficiency, program-synthesis; evalplus ships Docker support for self-hosted deployment; When you need advanced benchmarks specific to large language model generated program synthesis, such as from GPT-4 or ChatGPT. ### When should I choose LLMDebugger over evalplus? Choose LLMDebugger over evalplus when Pricing: Free for use, based on its open-source nature with an Apache-2.0 license.; Tags unique to LLMDebugger: acl'24, llm debugging, python debugger for ai, runtime verification; Also covers Developer Tools; When detailed step-by-step inspection of the runtime behavior of large language models is required, LLMDebugger can provide precise insights into each execution phase. ### When should I avoid evalplus? Avoid if you require broad language model benchmarking that is not specifically focused on program synthesis capabilities. Do not use evalplus if your project does not benefit from or need Docker-based isolation for code execution safety measures, such as in controlled lab environments without external dependencies. ### When should I avoid LLMDebugger? Avoid using if you are only interested in higher-level performance metrics rather than the intricate details of runtime behavior, as LLMDebugger emphasizes step-by-step execution. Not recommended for teams lacking experience with Python or specific to this tool's installation and usage workflow that involves setting up a Conda environment. ### Is evalplus or LLMDebugger more popular on GitHub? evalplus has more GitHub stars (1,794 vs 587). Stars measure visibility, not whether either tool fits your constraints. ### Are evalplus and LLMDebugger open source? Yes - both are open-source projects on GitHub (evalplus: Apache-2.0, LLMDebugger: Apache-2.0). ### Where can I find alternatives to evalplus or LLMDebugger? GraphCanon lists graph-backed alternatives at [evalplus alternatives](/tools/evalplus-evalplus/alternatives) and [LLMDebugger alternatives](/tools/floridsleeves-llmdebugger/alternatives) ([evalplus markdown twin](/tools/evalplus-evalplus/alternatives.md), [LLMDebugger markdown twin](/tools/floridsleeves-llmdebugger/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/evalplus-evalplus-vs-floridsleeves-llmdebugger.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, evalplus or LLMDebugger? evalplus: Slowing. LLMDebugger: Dormant. 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 evalplus and LLMDebugger? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [evalplus trust report](/tools/evalplus-evalplus/trust); [LLMDebugger trust report](/tools/floridsleeves-llmdebugger/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=evalplus-evalplus`](/api/graphcanon/graph?tool=evalplus-evalplus) - 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/_