Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents. Up to 4× faster than Apple's MLX (mlx-lm) on the same weights.
C-Rank Grade: A (Welcoming) - 69/100
External PR Merge Rate: 84%
Response Time: -
First Timer Success: 50%
raullenchai/Rapid-MLX has a recorded first-timer success rate of 50.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in raullenchai/Rapid-MLX respond to incoming external pull requests in approximately 0.0 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 68.6 places raullenchai/Rapid-MLX in the A tier.
The external contributor pull request merge rate for raullenchai/Rapid-MLX is 84.1%, based on public PR activity from non-core contributors.
raullenchai/Rapid-MLX does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents. Up to 4× faster than Apple's MLX (mlx-lm) on the same weights.
Highly welcoming maintainers in raullenchai/Rapid-MLX. Prompt code reviews with positive guidance for new contributors.
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/raullenchai/Rapid-MLX?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 22:00 UTC (22:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 21:00 to 01:00 UTC (21:00 - 01:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (96% approval). Large PRs (>500 lines) take ~115 hours (38% approval). Keep your diff compact for rapid review.
Background We've built a new token-level OutputRouter architecture that routes model output tokens into semantic channels (content/reasoning/tool_calls) based on token IDs read directly from the tokenizer vocabulary. This replaces the fragile regex-based approach. Current state: OutputRouter is implemented and working for Gemma 4 (PR branch feat/upstream-sync-march26) 17 unit tests + full E2E integration verified Old regex-based parsers remain as fallback for other models (Qwen3, DeepSeek, etc.) Architecture: Old (regex): model output text → strip_special_tokens(regex) → reasoning_parser(regex) → tool_parser(regex) New (tokens): model output token IDs → OutputRouter.feed(token_id) → Channel.CONTENT/REASONING/TOOL_CALL Key files: vllm_mlx/output_router.py — Core router (state machine + TokenMap + auto-detection from tokenizer) vllm_mlx/models/llm.py — Integration in stream_generate() tests/test_output_router.py — 17 unit tests as regression baseline Migration plan
Rate what actually matters after opening a pull request here.
Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.
When evaluating whether to contribute to raullenchai/Rapid-MLX, 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 raullenchai/Rapid-MLX acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 84.1% were successfully merged into the primary branch.
raullenchai/Rapid-MLX has a recorded first-timer success rate of 50.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. 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 68.6 places raullenchai/Rapid-MLX in the Welcoming tier.
The external pull request merge rate is 84.1%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
raullenchai/Rapid-MLX does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for raullenchai/Rapid-MLX 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.