Changelog / release

0.12.3 — A picker that answers “will this run on my Mac?”

Upgrade: pip install -U rapid-mlx · brew upgrade rapid-mlx · or grab the desktop app.

Gemma 4 checkpoints stopped serving at all. mlx-lm 0.31.x dropped mlx_lm/chat_templates/gemma4.py, while mlx-community/gemma-4-26b-a4b-it-4bit still declares "chat_template_type": "gemma4" in its tokenizer config. mlx-lm imports that module by name with no guard, so the import raised ModuleNotFoundError and rapid-mlx serve died at startup with no fallback to the checkpoint’s own chat_template.jinja — a regression against 0.6.71, which still shipped the module. Weights load before the tokenizer in mlx_lm.load, so a catch-and-retry would re-read multiple gigabytes; the offending field is neutralized up front instead (issue #1420, PR #1439).
The desktop app recommends a model by your Mac’s memory. The old five-role matrix (Coding / Chat / Vision / …) asked you to classify yourself before running anything. It is replaced by one RAM-tier table: per tier a smart pick — the most capable model that fits — and, where a genuinely faster model is worth a second card, a fast alternative. About 1,500 lines lighter (PR #1437).
The bundled app moves to 0.12.1, a signed release carrying engine 0.12.1 (PR #1433).