Gemma 4 26B A4B It 8bit

Usage

pip install -U mlx-vlm

python -m mlx_vlm.generate \
--model TyKaoz/gemma-4-26B-A4B-it-8bit \
--prompt "Explique la quantization en une phrase." \
--max-tokens 200

By TyKaoz — privacy-first native macOS LLM chat client. Apache 2.0, inherited from the base model.

--- license: apache-2.0 base_model: [google/gemma-4-26B-A4B-it] library_name: mlx pipeline_tag: image-text-to-text language: [en, fr] tags: [mlx, mlx-vlm, vlm, gemma4, gemma, moe, apple-silicon, quantized] --- # Gemma 4 26B-A4B Instruct (MoE) — 8-bit MLX 8-bit [MLX](https://github.com/ml-explore/mlx) quantization of [`google/gemma-4-26B-A4B-it`](https://huggingface.co/google/gemma-4-26B-A4B-it), for Apple Silicon (~26 GB). Sparse-MoE vision-language model — run it with `mlx-vlm`, not `mlx-lm`. The expert router (`router.proj`) is kept at 8-bit precision. ## Usage ```bash pip install -U mlx-vlm ``` ```bash python -m mlx_vlm.generate \ --model TyKaoz/gemma-4-26B-A4B-it-8bit \ --prompt "Explique la quantization en une phrase." \ --max-tokens 200 ``` | Base | Tool | Precision | Size | |------|------|-----------|------| | `google/gemma-4-26B-A4B-it` | `mlx-vlm` | 8-bit · group 64 (router 8-bit) | ~26 GB | By **[TyKaoz](https://www.tykaoz.bzh)** — privacy-first native macOS LLM chat client. Apache 2.0, inherited from the base model.