Comparison
LLM.swift vs Rapid-MLX
Verdict
Pick LLM.swift if lLM.swift is a cross-platform C++ library for Apple systems that simplifies local interaction with large language models; pick Rapid-MLX if rapid-MLX is a high-performance local AI engine optimized for Apple Silicon, providing faster inference times and support for tool calling, prompt caching, and reasoning separation. It serves as a drop-in replacement for.
Markdown twin · LLM.swift alternatives · Rapid-MLX alternatives
GraphCanon updated Sep 20, 2026
5views this month
vs
Trust & integrity
| Signal | LLM.swift | Rapid-MLX |
|---|---|---|
| Maintenance | Steady (62d since push) As of Sep 20, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | No public record from this source As of Oct 4, 2026 · openssf-scorecard@v1 |
Tagline
- LLM.swift
- LLM.swift enables local interaction with large language models for multiple Apple platforms.
- Rapid-MLX
- Fast local AI engine for Apple Silicon
Stars
- LLM.swift
- 877
- Rapid-MLX
- 3.8k
Forks
- LLM.swift
- 126
- Rapid-MLX
- 416
Open issues
- LLM.swift
- 10
- Rapid-MLX
- 54
Language
- LLM.swift
- Swift
- Rapid-MLX
- Python
Adopt for
- LLM.swift
- LLM.swift is a cross-platform C++ library for Apple systems that simplifies local interaction with large language models.
- Rapid-MLX
- Rapid-MLX is a high-performance local AI engine optimized for Apple Silicon, providing faster inference times and support for tool calling, prompt caching, and reasoning separation. It serves as a drop-in replacement for
Persona
- LLM.swift
- -
- Rapid-MLX
- -
Runtime
- LLM.swift
- -
- Rapid-MLX
- -
License
- LLM.swift
- MIT license allows for free use and distribution, both commercially and in open source projects, with attribution preferred but not mandatory.
- Rapid-MLX
- Other
Last pushed
- LLM.swift
- Jul 19, 2026
- Rapid-MLX
- Sep 18, 2026
Categories
- LLM.swift
- Inference & Serving
- Rapid-MLX
- Developer Tools, Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- LLM.swift
- Steady (60%)
- Rapid-MLX
- Very active (96%)
Days since push
- LLM.swift
- 62d
- Rapid-MLX
- 0d
Open issues (now)
- LLM.swift
- 10
- Rapid-MLX
- 54
Stars delta
- LLM.swift
- +12 (30d)
- Rapid-MLX
- +383 (30d)
Open issues delta
- LLM.swift
- +1 (30d)
- Rapid-MLX
- +6 (30d)
OpenSSF Scorecard
- LLM.swift
- Not queried
- Rapid-MLX
- No public record from this source
Full report
- LLM.swift
- Trust report
- Rapid-MLX
- Trust report
Choose LLM.swift if…
- LLM.swift is primarily Swift; Rapid-MLX is Python.
- License: LLM.swift is MIT, Rapid-MLX is Other.
- Pricing: Free to use under the MIT License. Premium support may vary..
- Tags unique to LLM.swift: gguf, ios, llm-inference, macos.
- Choose LLM.swift when you need to integrate large language model functionalities into apps targeting multiple Apple platforms, including macOS and mobile OSes.
When NOT to use LLM.swift
- Avoid LLM.swift if your application must run on non-Apple systems or if compatibility across various operating systems is prioritized over ease-of-use on Apple platforms.
- Do not use this library if you require advanced server-side functionalities, as it focuses specifically on local interactions within Apple’s ecosystem.
Choose Rapid-MLX if…
- Rapid-MLX is primarily Python; LLM.swift is Swift.
- License: Rapid-MLX is Other, LLM.swift is MIT.
- Tags unique to Rapid-MLX: apple-silicon, claude-code, cursor, deepseek.
- Also covers Developer Tools, LLM Frameworks.
- When you need a fast local AI engine specifically optimized for Apple Silicon devices, offering up to 4.2x faster performance compared to Ollama.
When NOT to use Rapid-MLX
- If you are using Cursor, as it routes BYOK requests through its own servers, which cannot reach a Rapid-MLX endpoint on localhost, unless you intentionally expose the server through a public HTTPS
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (eastriverlee/LLM.swift) · observed Sep 20, 2026
- GitHub forks (eastriverlee/LLM.swift) · observed Sep 20, 2026
- Last push (eastriverlee/LLM.swift) · observed Jul 19, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (raullenchai/Rapid-MLX) · observed Sep 20, 2026
- GitHub forks (raullenchai/Rapid-MLX) · observed Sep 20, 2026
- Last push (raullenchai/Rapid-MLX) · observed Sep 18, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: LLM.swift 877 · Rapid-MLX 3.8k (synced Sep 20, 2026).
Common questions
- What is the difference between LLM.swift and Rapid-MLX?
- LLM.swift: LLM.swift enables local interaction with large language models for multiple Apple platforms.. Rapid-MLX: Fast local AI engine for Apple Silicon. See the comparison table for live GitHub stats and shared categories.
- When should I choose LLM.swift over Rapid-MLX?
- Choose LLM.swift over Rapid-MLX when LLM.swift is primarily Swift; Rapid-MLX is Python; License: LLM.swift is MIT, Rapid-MLX is Other; Pricing: Free to use under the MIT License. Premium support may vary.; Tags unique to LLM.swift: gguf, ios, llm-inference, macos; Choose LLM.swift when you need to integrate large language model functionalities into apps targeting multiple Apple platforms, including macOS and mobile OSes.
- When should I choose Rapid-MLX over LLM.swift?
- Choose Rapid-MLX over LLM.swift when Rapid-MLX is primarily Python; LLM.swift is Swift; License: Rapid-MLX is Other, LLM.swift is MIT; Tags unique to Rapid-MLX: apple-silicon, claude-code, cursor, deepseek; Also covers Developer Tools, LLM Frameworks; When you need a fast local AI engine specifically optimized for Apple Silicon devices, offering up to 4.2x faster performance compared to Ollama.
- When should I avoid LLM.swift?
- Avoid LLM.swift if your application must run on non-Apple systems or if compatibility across various operating systems is prioritized over ease-of-use on Apple platforms. Do not use this library if you require advanced server-side functionalities, as it focuses specifically on local interactions within Apple’s ecosystem.
- When should I avoid Rapid-MLX?
- If you are using Cursor, as it routes BYOK requests through its own servers, which cannot reach a Rapid-MLX endpoint on localhost, unless you intentionally expose the server through a public HTTPS
- Is LLM.swift or Rapid-MLX more popular on GitHub?
- Rapid-MLX has more GitHub stars (3,774 vs 877). Stars measure visibility, not whether either tool fits your constraints.
- Are LLM.swift and Rapid-MLX open source?
- Yes - both are open-source projects on GitHub (LLM.swift: MIT, Rapid-MLX: Other).
- Where can I find alternatives to LLM.swift or Rapid-MLX?
- GraphCanon lists graph-backed alternatives at LLM.swift alternatives and Rapid-MLX alternatives (LLM.swift markdown twin, Rapid-MLX markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, LLM.swift or Rapid-MLX?
- LLM.swift: Steady. Rapid-MLX: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for LLM.swift and Rapid-MLX?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLM.swift trust report; Rapid-MLX trust report.