PyTorch native quantization for training and inference
C-Rank Grade: A (Welcoming) - 56/100
External PR Merge Rate: 45%
Response Time: 1d
First Timer Success: 29%
pytorch/ao has a recorded first-timer success rate of 28.8%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in pytorch/ao respond to incoming external pull requests in approximately 25.4 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 56.2 places pytorch/ao in the A tier.
The external contributor pull request merge rate for pytorch/ao is 44.6%, based on public PR activity from non-core contributors.
pytorch/ao currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Balanced & professional review environment in pytorch/ao. Maintains strict focus on technical quality and test standards.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/pytorch/ao?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
Calculating local time...
Calculating local time...
Detected: UTC
Maintainers are most responsive around 19:00 UTC (19:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 16:00 to 20:00 UTC (16:00 - 20:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (56% approval). Large PRs (>500 lines) take ~122 hours (20% approval). Keep your diff compact for rapid review.
in docs/ make html /data/users/jerryzh/ao/docs/source/api_reference/api_ref_float8.rst:10: WARNING: Title underline too short. Main float8 training APIs ---------------------- /data/users/jerryzh/ao/docs/source/api_reference/api_ref_qat.rst:10: ERROR: Unknown target name: "quantize". /data/users/jerryzh/ao/docs/source/api_reference/api_ref_quantization.rst:5: WARNING: duplicate label api_quantization, other instance in /data/users/jerryzh/ao/docs/source/api_reference/api_ref_float8.rst /data/users/jerryzh/ao/docs/source/api_reference/api_ref_utils.rst:31: ERROR: Unknown target name: "torchao.quantization.quantize". /data/users/jerryzh/ao/docs/source/api_reference/api_ref_utils.rst:36: ERROR: Unknown target name: "quantize". /home/jerryzh/.conda/envs/vllm/lib/python3.12/site-packages/torchao/quantization/quant_api.py:docstring of torchao.quantization.quant_api.FqnToConfig:5: ERROR: Unexpected indentation. /home/jerryzh/.conda/envs/vllm/lib/python3.12/site-packages/torchao/quantization/
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When evaluating whether to contribute to pytorch/ao, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of pytorch/ao acknowledge new external contributions in approximately 1 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 44.6% were successfully merged into the primary branch.
pytorch/ao has a recorded first-timer success rate of 28.8%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~1 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 56.2 places pytorch/ao in the Welcoming tier.
The external pull request merge rate is 44.6%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, pytorch/ao currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for pytorch/ao are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.