--- title: "evalplus vs EAGLE" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evalplus-evalplus-vs-safeailab-eagle" tools: ["evalplus-evalplus", "safeailab-eagle"] --- # evalplus vs EAGLE *GraphCanon updated Aug 24, 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 EAGLE if eAGLE offers official implementations for its series of large language models with emphasis on inference and speculative decoding. [evalplus](https://evalplus.github.io) reports 1.8k GitHub stars, 205 forks, and 71 open issues, last pushed Oct 2, 2025. [EAGLE](https://arxiv.org/pdf/2503.01840) has 2.5k stars, 297 forks, and 101 open issues, last pushed Feb 20, 2026. Figures are from public GitHub metadata via [evalplus's repository](https://github.com/evalplus/evalplus) and [EAGLE's repository](https://github.com/SafeAILab/EAGLE). | | [evalplus](/tools/evalplus-evalplus.md) | [EAGLE](/tools/safeailab-eagle.md) | | --- | --- | --- | | Tagline | Rigorous evaluation of LLM-synthesized code | Official Implementation of EAGLE Series Models | | Stars | 1,794 | 2,510 | | Forks | 205 | 297 | | Open issues | 71 | 101 | | 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. | EAGLE offers official implementations for its series of large language models with emphasis on inference and speculative decoding. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Evaluation & Observability | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [evalplus](/tools/evalplus-evalplus.md) | [EAGLE](/tools/safeailab-eagle.md) | | --- | --- | --- | | Days since push | 306d | 155d | | Open issues (now) | 71 | 101 | | Full report | [trust report](/tools/evalplus-evalplus/trust.md) | [trust report](/tools/safeailab-eagle/trust.md) | ## Shared compatibility - **Python**: [evalplus](/tools/evalplus-evalplus.md) - Python runtime; [EAGLE](/tools/safeailab-eagle.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: EAGLE - **Adopt for:** EAGLE offers official implementations for its series of large language models with emphasis on inference and speculative decoding. ## Choose when ### Choose evalplus if… - License: evalplus is Apache-2.0, EAGLE is Other. - Tags unique to evalplus: benchmark, chatgpt, efficiency, program-synthesis. - Also covers Evaluation & Observability. - 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 EAGLE if… - License: EAGLE is Other, evalplus is Apache-2.0. - Tags unique to EAGLE: large language models, llm-inference, speculative-decoding. - Also covers Inference & Serving, LLM Frameworks. - If your project requires the latest advancements in model capabilities from ICML'24, EMNLP'24, and NeurIPS'25 as provided by EAGLE-1, EAGLE-2, or EAGLE-3. ## 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 EAGLE - If the specific advancements and techniques implemented in ICML'24 papers are not relevant to your project. - In cases where speculative decoding does not align with the goals or methods of your application, opting for EAGLE may not be beneficial. ## Common questions ### What is the difference between evalplus and EAGLE? evalplus: Rigorous evaluation of LLM-synthesized code. EAGLE: Official Implementation of EAGLE Series Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose evalplus over EAGLE? Choose evalplus over EAGLE when License: evalplus is Apache-2.0, EAGLE is Other; Tags unique to evalplus: benchmark, chatgpt, efficiency, program-synthesis; Also covers Evaluation & Observability; 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 EAGLE over evalplus? Choose EAGLE over evalplus when License: EAGLE is Other, evalplus is Apache-2.0; Tags unique to EAGLE: large language models, llm-inference, speculative-decoding; Also covers Inference & Serving, LLM Frameworks; If your project requires the latest advancements in model capabilities from ICML'24, EMNLP'24, and NeurIPS'25 as provided by EAGLE-1, EAGLE-2, or EAGLE-3. ### 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 EAGLE? If the specific advancements and techniques implemented in ICML'24 papers are not relevant to your project. In cases where speculative decoding does not align with the goals or methods of your application, opting for EAGLE may not be beneficial. ### Is evalplus or EAGLE more popular on GitHub? EAGLE has more GitHub stars (2,510 vs 1,794). Stars measure visibility, not whether either tool fits your constraints. ### Are evalplus and EAGLE open source? Yes - both are open-source projects on GitHub (evalplus: Apache-2.0, EAGLE: Other). ### Where can I find alternatives to evalplus or EAGLE? GraphCanon lists graph-backed alternatives at [evalplus alternatives](/tools/evalplus-evalplus/alternatives) and [EAGLE alternatives](/tools/safeailab-eagle/alternatives) ([evalplus markdown twin](/tools/evalplus-evalplus/alternatives.md), [EAGLE markdown twin](/tools/safeailab-eagle/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-safeailab-eagle.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, evalplus or EAGLE? evalplus: Slowing. EAGLE: Slowing. 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 EAGLE? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [evalplus trust report](/tools/evalplus-evalplus/trust); [EAGLE trust report](/tools/safeailab-eagle/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/_