MLX LM
AppleMLX LM generates text with large language models on Apple silicon using MLX, pulling any of thousands of compatible models from the Hugging Face Hub. It ships CLI commands for generation, chat, a server and quantized model conversion, with prompt caching, a rotating KV cache and distributed inference and fine-tuning through mx.distributed. Apple's ml-explore organization maintains it as the LM layer split out of the core mlx repo.
Openness
5 high confidence- license
- MIT(OSI)
- source
- public
- core features withheld
- no — no enterprise or paid tier
The LICENSE body is the stock MIT text, "Copyright (c) 2023 Apple Inc.", read in full. The repository is public and unarchived and builds the published package; nothing in the README names a paid tier, hosted build or withheld component, so the core reads as ungated.
- https://api.github.com/repos/ml-explore/mlx-lm recorded 2026-09-01
Repo metadata for ml-explore/mlx-lm - archived false, license MIT, 6,853 stars, pushed 2026-09-01.
- https://raw.githubusercontent.com/ml-explore/mlx-lm/main/LICENSE recorded 2026-10-07
LICENSE body, read in full: stock MIT text, "Copyright (c) 2023 Apple Inc.", no appended condition.
- https://raw.githubusercontent.com/ml-explore/mlx-lm/main/README.md recorded 2026-10-07
README, read for a paid tier or gated build (none found) and for the product's shape: "MLX LM is a Python package for generating text and fine-tuning large language models on Apple silicon with MLX"; generation/chat/server CLI, HF Hub integration, quantization and upload, distributed inference and fine-tuning with mx.distributed.
Adoption
3 high confidencePyPI downloads of the mlx-lm package, which backlinks to this repository, are the measured adoption signal. A conda-forge distribution also exists and is not counted here, so the figure is a floor across one of two channels rather than the full total.
- https://pypi.org/pypi/mlx-lm/json recorded 2026-09-01
home_page = https://github.com/ml-explore/mlx-lm; version 0.31.3; summary "LLMs with MLX and the Hugging Face Hub".
- https://pypistats.org/api/packages/mlx-lm/recent recorded 2026-10-07
544,885 downloads in the trailing 30 days for mlx-lm (pypistats last_month)
Capability
3 medium confidenceMLX LM sits two tiers below vLLM, level with Uzu, llamafile and the other single-target local engines: it serves one hardware family and carries none of the datacenter parallelism or disaggregation that the higher tiers are built around. Within the Apple-silicon niche it is the reference LM runtime, a distinction the adoption axis credits rather than this one.
- https://raw.githubusercontent.com/ml-explore/mlx-lm/main/README.md recorded 2026-10-07
README feature list: HF Hub integration, quantization and upload, LoRA and full fine-tuning, distributed inference and fine-tuning with mx.distributed, prompt caching, rotating fixed-size KV cache, prefill step size, mlx_lm.server.
Verified 2026-10-07, except some scores, still awaiting re-confirmation