mlx-lm
Shares rank 26 of 27 inference engines by recommenders
People recommend it for fast local model inference on Apple Silicon Macs. The main caveat is that main-branch builds have crashed or failed with some models.
People recommend it for fast local model inference on Apple Silicon Macs. The main caveat is that main-branch builds have crashed or failed with some models.
6 people gave an opinion
- recommend it
- 5
- criticize it
- 1
- approval share
- 83%
Recommended in 4 of 13 months
- November 2025: not recommended
- December 2025: recommended
- January 2026: not recommended
- February 2026: recommended
- March 2026: recommended
- April 2026: recommended
- May 2026: not recommended
- June 2026: not recommended
- July 2026: not recommended
- August 2026: not 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.
- 5 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 4 of 13 monthsNeeds 4 or more, 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
Strong performance on M-series chips
“the performance on M-series chips has been genuinely impressive”
Comment from 31 Mar 2026 in “Ollama is now powered by MLX on Apple Silicon in preview” Works well on Macs
“I've had good performance with that on Macs.”
Comment from 28 Feb 2026 in “Qwen3.5 122B and 35B models offer Sonnet 4.5 performance on local computers” Version 0.30.0 works fine
“mlx_lm==0.30.0 will serve you fine”
Comment from 16 Dec 2025 in “Nvidia Nemotron 3 Family of Models” Bugs get fixed on main
“That too was broken in mlx-lm (it crashed), but has since been fixed on the main branch”
Comment from 13 Apr 2026 in “I ran Gemma 4 as a local model in Codex CLI”
What people warn about
Each mark is one comment
Crashed on main branch
“That too was broken in mlx-lm (it crashed), but has since been fixed on the main branch”
Comment from 13 Apr 2026 in “I ran Gemma 4 as a local model in Codex CLI” Gemma models failed to run
“I have got zero success running gemma with mlx-lm main branch.”
Comment from 13 Apr 2026 in “I ran Gemma 4 as a local model in Codex CLI”
Other inference engines people recommend
The four most recommended other inference engines, 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 |
|---|---|---|---|---|---|---|
| vLLM | 112 | 56 | 67% | 12 | — | Approved |
| Strata | 31 | 15 | 67% | 5 | — | Approved |
| DwarfStar 4 | 26 | 2 | 93% | 6 | — | Approved |
| SGLang | 19 | 13 | 59% | 8 | — | — |
| mlx-lmThis page | 5 | 1 | 83% | 4 | — | — |
What people said
5 of the 6 comments that mention it, newest first. Each links to the original comment.
“I have got zero success running gemma with mlx-lm main branch.”
“That too was broken in mlx-lm (it crashed), but has since been fixed on the main branch”
“the performance on M-series chips has been genuinely impressive”
“I've had good performance with that on Macs.”
“mlx_lm==0.30.0 will serve you fine”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.