vMLX
Shares rank 23 of 27 local LLM runners by recommenders
Free app built for performance on Apple Silicon Macs, using unified memory and NVMe caching. Main caveat: limited support for some models, such as gpt-oss.
Free app built for performance on Apple Silicon Macs, using unified memory and NVMe caching. Main caveat: limited support for some models, such as gpt-oss.
5 people gave an opinion
- recommend it
- 5
- criticize it
- 0
- approval share
- 100%
Recommended in 3 of 13 months
- November 2025: not recommended
- December 2025: not recommended
- January 2026: not recommended
- February 2026: not recommended
- March 2026: recommended
- April 2026: recommended
- May 2026: not recommended
- June 2026: not recommended
- July 2026: not recommended
- August 2026: recommended
- September 2026: not recommended
- October 2026: not recommended
- November 2026: not recommended (month in progress)
Why it doesn’t carry the badge
- 5 people recommend itNeeds 10 or more, not met.
- Nobody criticizes itNeeds 2 to 1 or better, met.
- Recommended in 3 of 13 monthsNeeds 4 or more, not met.
The same three rules apply to every product, and the badge can’t be bought. How the badge works
What people say about it
The reasons people give, with the number of comments that give each one. Open a reason to read what they said.
Why people recommend it
Each mark is one comment
Performance optimizations for Apple Silicon
“both great projects that offer some amazing performance optimizations for Apple Silicon that utilize UMA and NVME caching efficiently”
Comment from 10 Aug 2026 in “Meta Muse Glimmer – open weights 30B local coding model” “every local AI app on Mac left performance on the table”
Comment from 9 Mar 2026 on Hacker News Recommended for Apple Silicon Macs
“both great projects that offer some amazing performance optimizations for Apple Silicon that utilize UMA and NVME caching efficiently”
Comment from 10 Aug 2026 in “Meta Muse Glimmer – open weights 30B local coding model” “Check out vMLX if you use Apple Silicon.”
Comment from 9 Apr 2026 in “Running Google Gemma 4 Locally with LM Studio's New Headless CLI and Claude Code” Uses unified memory and NVMe caching
“both great projects that offer some amazing performance optimizations for Apple Silicon that utilize UMA and NVME caching efficiently”
Comment from 10 Aug 2026 in “Meta Muse Glimmer – open weights 30B local coding model”
What people warn about
Each mark is one comment
Limited support for some models
“vmlx doesn't have extensive support for some models like gpt-oss”
Comment from 5 Apr 2026 on Hacker News
Other local LLM runners people recommend
The four most recommended other local LLM runners, with the same counts for each, so you can compare like for like. The tick on each bar marks the 2 to 1 line the badge needs.
| Product | Recommend | Criticize | Approval | Months | Owned | Badge |
|---|---|---|---|---|---|---|
| llama.cpp | 471 | 109 | 81% | 13 | 1 yr4 owners | Approved |
| Ollama | 350 | 247 | 59% | 12 | 1.5 yrs8 owners | — |
| LM Studio | 217 | 74 | 75% | 12 | 3 yrs4 owners | Approved |
| DS4 by antirez | 109 | 20 | 84% | 7 | 1 mo3 owners | Approved |
| vMLXThis page | 5 | 0 | 100% | 3 | — | — |
What people said
4 of the 5 comments that mention it, newest first. Each links to the original comment.
“both great projects that offer some amazing performance optimizations for Apple Silicon that utilize UMA and NVME caching efficiently”
“Check out vMLX if you use Apple Silicon.”
“vmlx doesn't have extensive support for some models like gpt-oss”
“every local AI app on Mac left performance on the table”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.