What is CLM? If you've seen TypeSafe AI's "Jev" — it's a similar idea: instead of generating text, the model just returns a typed answer with a probability, so it's much faster and cheaper than a normal LLM for yes/no or multiple-choice type decisions. Jev is a closed, proprietary, API-only product. This CLM port does the same kind of thing (that's literally what the original CLM paper calls itself — a "System One model"), but the weights are open (Apache-2.0) and it runs fully on your own Mac, free, with no API calls. Details Ported CLM (https://github.com/Contrastive-LM/CLM) — a frozen Qwen3-8B encoder + tiny fp32 heads that answers yes/no, choice, and score questions by embedding similarity instead of generating text — to Apple MLX. 8-bit checkpoint, 7.5 GiB, runs at ~336 tok/s / 9 GB peak on an M3 Pro. Checked against the authors' own vLLM server on 778 questions: 99.0% top-1 agreement, within their own run-to-run noise. Unofficial community port, not reviewed by the CLM authors. Weights + clm_mlx code (Apache-2.0): [https://huggingface.co/RealityCat/CLM-v0.1-8B-MLX-8bit] Standard MLX Qwen3 weights under the hood, so also usable with general MLX tooling ([mlx-workflow](https://www.connectcode.net/mlx-workflow.html)/[MLXUI](https://www.connectcode.net/mlxui_local_llm_ai_browser.html/%5BMLXUI%5D(https://www.connectcode.net/mlxui_local_llm_ai_browser.html))) beyond the CLM heads.   submitted by   /u/WebAssemblyMan [link]   [comments]