Benchmark Almanac

GitTaskBench

Claude 3.7 Sonnet 48.1% leads since August 2025
Not in model cards

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.

Abstract of GitTaskBench: A Benchmark for Code Agents Solving Real-World Tasks Through Code Repository Leveraging (arXiv:2508.18993, CC0)
11
Entries on its own leaderboard, 10 models we track

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:

  1. 1 Claude 3.7 Sonnet 48.1%
  2. 2 GPT-4.1 42.6%
  3. 3 Claude 3.5 Sonnet 40.7%
  4. 4 GPT-4o Aug 2024, max_iteration=100 37%
  5. 5 Gemini 2.5 Pro (snapshot unspecified) 35.2%
  6. 6 Qwen3-32B thinking 29.6%
  7. 7 DeepSeek-V3 Mar 2025 26.9%
  8. 8 o3-mini medium 22.2%
  9. 9 Llama 3.3 70B 20.4%
  10. 10 Qwen3-14B non-thinking 5.56%
  11. 11 Qwen3-8B non-thinking 1.85%

Source: Official GitTaskBench leaderboard

#EntryScoreSettingDateSource
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 Qwen3-32B 29.6% thinking, OpenHands Apr 2025 Official leaderboard
7 DeepSeek-V3 Mar 2025 26.9% OpenHands Mar 2025 Official leaderboard
8 o3-mini 22.2% medium, OpenHands Jan 2025 Official leaderboard
9 Llama 3.3 70B 20.4% OpenHands Dec 2024 Official leaderboard
10 Qwen3-14B 5.56% non-thinking, OpenHands Apr 2025 Official leaderboard
11 Qwen3-8B 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.

OpenAI Anthropic DeepSeek Cost frontier One model at each effort level
0% 10% 20% 30% 40% 50% $0.001 $0.01 $0.10 $1.00 $10 $100 Cost per task, log scale Claude 3.7 Sonnet GPT-4.1 GPT-4.1 o3-mini, medium DeepSeek-V3 0% 10% 20% 30% 40% 50% $0.001 $0.01 $0.10 $1.00 $10 $100 Cost per task, log scale Claude 3.7 Sonnet GPT-4.1

Source: Official GitTaskBench leaderboard

ModelEffortHarnessScoreCost per taskOutput 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
Qwen3-32B thinking OpenHands 29.6% 8,755
DeepSeek-V3 Mar 2025 OpenHands 26.9% $1.31 31,958
Qwen3-32B 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
Llama 3.3 70B OpenHands 20.4% 873
o3-mini medium SWE-Agent 20.4% $0.17 215
Llama 3.3 70B SWE-Agent 18.5% 1,986
DeepSeek-V3 Mar 2025 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
DeepSeek-V3 Mar 2025 SWE-Agent 12% $0.11 1,650
Qwen3-32B 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
Qwen3-14B non-thinking OpenHands 5.56% 2,540
Qwen3-32B non-thinking SWE-Agent 3.70% 2,405
GPT-4o Aug 2024 Aider 1.85% $0.03 493
Qwen3-8B 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.

Anthropic
Own leaderboard Not tested since Aug 2025

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.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2024 2025 Near the ceiling (85%) Claude 3.7 Sonnet Claude 3.5 Sonnet 0% 20% 40% 60% 80% 100% 2024 2025 Near the ceiling (85%) Claude 3.7 Sonnet Claude 3.5 Sonnet

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.

More in Coding

All 282 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%
  • 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%
  • SWE-bench Multilingual In use 300 GitHub-issue tasks across nine programming languages in SWE-bench format. Patch graded by repository tests. Claude Fable 5.2 96.6%
  • 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