HumanEvalPack
Cohere Command A 76.2% leads since Apr 2025 Only in system cards Models write functions for HumanEval problems translated into Python, JavaScript, Java, Go, C++ and Rust. Hidden tests give pass@1.
The pack also has code repair and explanation tasks. Labs usually report the synthesize task.
- Level
- University Undergraduates and entry-level professionals
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Code A program or patch run against tests.
Cohere Command A leads with 76.2% among models released by Mar 2025
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
The newest model with a score here came out in Mar 2025, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- GPT-6 Astra
- Claude Opus 5.5
- GPT-6.1 Terra
- GPT-6.1 Sol
- and 16 more
- 1 Cohere Command A 76.2%
- 2
Qwen-14B 33.7% - 3 Qwen-7B 24.2%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Cohere Command A | 76.2% | Apr 2025 | Model card | |
| 2 | Qwen-14B | 33.7% | Sep 2023 | Model card | |
| 3 | Qwen-7B | 24.2% | Sep 2023 | Model card |
2 models have held number one since its release in Aug 2023
Lab claims count from the day the card came out, independent runs from the model’s release.
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
3 system cards report it, from 2 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 1 Apr 2025 | Cohere Command A technical report | 76.2 | HE (All), HumanEval in six languages (Table 12, Table 26) | Capabilities |
| 28 Sep 2023 | Qwen-7B technical report | 24.2 | HumanEvalPack (synthesize) zero-shot pass@1 average: Python 37.2, JavaScript 23.2, Java 32.9, Go 20.7, C++ 22.0, Rust 9.1 (Table 11) | Capabilities |
| 28 Sep 2023 | Qwen-14B technical report | 33.7 | HumanEvalPack (synthesize) zero-shot pass@1 average: Python 43.9, JavaScript 38.4, Java 42.7, Go 34.1, C++ 24.4, Rust 18.9 (Table 11) | Capabilities |
More in Coding
- SWE-bench Verified In use 500 human-validated GitHub issues from 12 Python repos. Agent writes a patch that must pass hidden tests. Claude Opus 4.7 83.5%
- SWE-bench Multilingual In use 300 GitHub-issue tasks across nine programming languages in SWE-bench format. Patch graded by repository tests. Claude Opus 5.5 93.9%
- LiveCodeBench v6 In use Competitive programming problems collected after model cutoffs from LeetCode, AtCoder, Codeforces. Scored pass@1 on hidden tests.
DeepSeek-V4-Pro 93.5% - DeepSWE In use 113 original long-horizon engineering tasks across 91 repos and five languages, written from scratch. Hand-written verifiers accept alternative solutions. GPT-6 Astra 74.1%
- SciCode In use Scientist-curated research coding problems split into subproblems across natural sciences. Code checked against test cases.
Seed2.1 Pro 59.8% - Codeforces rating In use Model solves recent Codeforces contest problems. An Elo-style rating is computed from simulated contest performance. DeepSeek V4.1 Flash 3,471