GitTaskBench
Code agents solve 54 real tasks across 7 modalities and 7 domains by using a given GitHub repository, from understanding and setup to running it.
About 260 GitHub stars.
- Made by
- QuantaAlpha
- Released
- August 2025
- Kind
- Fixing real repositories
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
- Strongest model tested
- Claude 3.7 Sonnet #118 on the capability index
- Last model added
- April 2025
- Scores refreshed
- November 12th, 2026
In the authors’ words
Beyond scratch coding, exploiting large-scale code repositories (e.g., GitHub) for practical tasks is vital in real-world software development, yet current benchmarks rarely evaluate code agents in such authentic, workflow-driven scenarios. To bridge this gap, we introduce GitTaskBench, a benchmark designed to systematically assess this capability via 54 realistic tasks across 7 modalities and 7 domains. Each task pairs a relevant repository with an automated, human-curated evaluation harness specifying practical success criteria. Beyond measuring execution and task success, we also propose the alpha-value metric to quantify the economic benefit of agent performance, which integrates task success rates, token cost, and average developer salaries. Experiments across three state-of-the-art agent frameworks with multiple advanced LLMs show that leveraging code repositories for complex task solving remains challenging: even the best-performing system, OpenHands+Claude 3.7, solves only 48.15% of tasks (recent progress has pushed the frontier further, with RepoMaster+Claude 3.5 achieving a new record of 62.96%). Error analysis attributes over half of failures to seemingly mundane yet critical steps like environment setup and dependency resolution, highlighting the need for more robust workflow management and increased timeout preparedness. By releasing GitTaskBench, we aim to drive progress and attention toward repository-aware code reasoning, execution, and deployment – moving agents closer to solving complex, end-to-end real-world tasks. The benchmark and code are open-sourced at https://github.com/QuantaAlpha/GitTaskBench.
Claude 3.7 Sonnet leads with 48.1% among models released by April 2025
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Every run is in the next chart. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
The newest model with a score here came out in April 2025, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 16 more
- 1 Claude 3.7 Sonnet 48.1%
- 2 GPT-4.1 42.6%
- 3 Claude 3.5 Sonnet 40.7%
- 4 GPT-4o Aug 2024, max_iteration=100 37%
- 5 Gemini 2.5 Pro (snapshot unspecified) 35.2%
- 6
Qwen3-32B thinking 29.6%
- 7
DeepSeek-V3 Mar 2025 26.9%
- 8 o3-mini medium 22.2%
- 9
Llama 3.3 70B 20.4%
- 10
Qwen3-14B non-thinking 5.56%
- 11
Qwen3-8B non-thinking 1.85%
Source: Official GitTaskBench leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude 3.7 Sonnet | 48.1% | OpenHands | Feb 2025 | Official leaderboard |
| 2 | GPT-4.1 | 42.6% | OpenHands | Apr 2025 | Official leaderboard |
| 3 | Claude 3.5 Sonnet | 40.7% | OpenHands | Jun 2024 | Official leaderboard |
| 4 | GPT-4o Aug 2024 | 37% | max_iteration=100, OpenHands | Aug 2024 | Official leaderboard |
| 5 | Gemini 2.5 Pro (snapshot unspecified) | 35.2% | OpenHands | Official leaderboard | |
| 6 | | 29.6% | thinking, OpenHands | Apr 2025 | Official leaderboard |
| 7 | | 26.9% | OpenHands | Mar 2025 | Official leaderboard |
| 8 | o3-mini | 22.2% | medium, OpenHands | Jan 2025 | Official leaderboard |
| 9 | | 20.4% | OpenHands | Dec 2024 | Official leaderboard |
| 10 | | 5.56% | non-thinking, OpenHands | Apr 2025 | Official leaderboard |
| 11 | | 1.85% | non-thinking, OpenHands | Apr 2025 | Official leaderboard |
The best score, 48.1%, costs $30 a task
Runs on the cost frontier score higher than any run that's cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.
Source: Official GitTaskBench leaderboard
| Model | Effort | Harness | Score | Cost per task | Output tokens |
|---|---|---|---|---|---|
| Claude 3.7 Sonnet | OpenHands | 48.1% | $30 | 85,033 | |
| Claude 3.7 Sonnet | SWE-Agent | 42.6% | $1.67 | 808 | |
| GPT-4.1 | OpenHands | 42.6% | $0.94 | 1,535 | |
| Claude 3.5 Sonnet | OpenHands | 40.7% | $8.95 | 24,929 | |
| GPT-4o Aug 2024 | max_iteration=100 | OpenHands | 37% | $4.10 | 12,053 |
| GPT-4o Aug 2024 | timeout=1200 s | OpenHands | 35.2% | $2.65 | 8,207 |
| GPT-4o Aug 2024 | timeout=1800 s | OpenHands | 35.2% | $6.52 | 15,558 |
| GPT-4o Aug 2024 | max_iteration=30 | OpenHands | 33.3% | $2.67 | 8,532 |
| GPT-4o Aug 2024 | max_iteration=70 | OpenHands | 33.3% | $3.96 | 9,158 |
| GPT-4.1 | SWE-Agent | 31.5% | $0.66 | 2,098 | |
| | thinking | OpenHands | 29.6% | 8,755 | |
| | OpenHands | 26.9% | $1.31 | 31,958 | |
| | non-thinking | OpenHands | 25.9% | 2,098 | |
| Claude 3.5 Sonnet | SWE-Agent | 22.2% | $1.38 | 943 | |
| o3-mini | medium | OpenHands | 22.2% | $3.58 | 183,638 |
| | OpenHands | 20.4% | 873 | ||
| o3-mini | medium | SWE-Agent | 20.4% | $0.17 | 215 |
| | SWE-Agent | 18.5% | 1,986 | ||
| | Aider | 16.7% | $0.003 | 600 | |
| GPT-4o Aug 2024 | OpenHands | 14.8% | $1.94 | 3,990 | |
| Claude 3.5 Sonnet | Aider | 13% | $0.03 | 534 | |
| GPT-4o Aug 2024 | timeout=120 s | OpenHands | 13% | $0.68 | 1,805 |
| | SWE-Agent | 12% | $0.11 | 1,650 | |
| | thinking | SWE-Agent | 11.1% | 559 | |
| GPT-4o Aug 2024 | SWE-Agent | 10.2% | $0.78 | 1,283 | |
| GPT-4.1 | Aider | 7.41% | $0.04 | 734 | |
| | non-thinking | OpenHands | 5.56% | 2,540 | |
| | non-thinking | SWE-Agent | 3.70% | 2,405 | |
| GPT-4o Aug 2024 | Aider | 1.85% | $0.03 | 493 | |
| | non-thinking | OpenHands | 1.85% | 2,045 |
Number one over time
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Official GitTaskBench leaderboard
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official GitTaskBench leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
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