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Rapid-MLX

The fastest local AI engine for Apple Silicon. 4.2x faster than Ollama, 0.08s cached TTFT, 100% tool calling. 17 tool parsers, prompt cache, reasoning separation, cloud routing.

Our verdict

Not reviewed yet

We have not reviewed Rapid-MLX yet

No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.

How we review records

From the listing

About Rapid-MLX

Rapid-MLX is a local AI inference engine optimized for Apple Silicon, offering drop-in OpenAI API compatibility. It achieves 4.2x faster performance than Ollama with 0.08s cached time-to-first-token and 100% tool calling support. The engine includes 17 tool parsers, prompt caching, reasoning separation, and cloud routing for hybrid local/remote execution.

Best for

Developers on Apple Silicon who need a fast, local OpenAI-compatible inference engine for tool-calling and reasoning tasks.

Use cases

  • Running local LLMs with OpenAI-compatible endpoints for tools like Claude Code or Cursor
  • Accelerating tool-calling workflows with 17 built-in parsers and cached responses
  • Offloading reasoning tasks locally while routing other requests to cloud models

Notes

2,641 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Pros

  • Significantly faster than Ollama on Apple Silicon hardware
  • Full OpenAI API compatibility simplifies integration with existing tools
  • Includes advanced features like prompt caching and reasoning separation out of the box

Cons

  • Limited to Apple Silicon hardware, excluding Intel Macs and other platforms
  • Community-maintained project may have less support than commercial alternatives
  • Performance gains depend on model caching and may not apply to all workloads

Key facts

What we have checked

Latest version
0.16.8 (released 22 Oct 2026)
Checked GitHub
GitHub stars
3,845
Checked github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438

Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.

Stars and usage

How Rapid-MLX is growing

GitHub stars

2,641 to 3,845

stars. 12 July 2026 to 26 Sept 2026, 2 readings.

Source: github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438. Checked .

Alternatives

Alternatives to Rapid-MLX

RecordTypeHow we knowChecked
llama.cppThis is an alternative to itAppNamed in the listingNot dated
OllamaThis is an alternative to itOpen sourceNamed in the listingNot dated
vLLMThis is an alternative to itOpen sourceNamed in the listingNot dated

Compare

Compare Rapid-MLX side by side

Sources

Where this comes from

  • GitHubOfficial

    Checked · Latest version

  • github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry

    Checked · GitHub stars

A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.

Changelog

What changed

  1. Released 0.16.8

    Source: GitHub

  2. Released rapid-mac-v0.16.8

    Source: GitHub

  3. Released 0.16.7

    Source: GitHub

  4. Released rapid-mac-v0.16.7

    Source: GitHub

  5. Released 0.16.6

    Source: GitHub

  6. Released rapid-mac-v0.16.6

    Source: GitHub

  7. Released 0.16.5

    Source: GitHub

  8. Released rapid-mac-v0.16.5

    Source: GitHub

  9. Released 0.16.4

    Source: GitHub

  10. Released rapid-mac-v0.16.4

    Source: GitHub

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