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Sawfwair/gemma-4-12B-it-MLX-4bit
gemma-4-12B-it-MLX-4bit is a image-text-to-text model from Sawfwair. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
This repository is Sawfwair's reproducible Apple Silicon conversion of google/gemma-4-12B-it. It is a quantized derivative, not a new base model or fine-tune.
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From the Hugging Face model README
This repository is Sawfwair's reproducible Apple Silicon conversion of
google/gemma-4-12B-it.
It is a quantized derivative, not a new base model or fine-tune.
The checkpoint was converted with MLX-VLM because Gemma 4 12B uses the unified
multimodal architecture (gemma4_unified). The package preserves the vision
and audio paths, Google's pinned July 2026 processor/tokenizer metadata, the
262,144-token context configuration, and the canonical tool-capable chat
template.
| Field | Value |
|---|---|
| Source | google/gemma-4-12B-it |
| Source revision | 12ace6d648d72bd41519e140f1185f34d38c7e3d |
| Source weight | model.safetensors — 23,919,549,408 bytes |
| Source SHA-256 | 5a84cb313260ac447237b890387116dfa8682e49a6b44bc585ae8353abbff18d |
| Quantization | MLX affine 4-bit, group size 64 |
| Compute dtype | bfloat16 |
| Converter | scripts/model-conversion/convert_gemma4_12b_mlx.py |
| Source commit | 347e65b6b774d7dc9f066f1fc01c82d4aa0ae9c9 |
The committed converter pins Python and all serialization dependencies, checks
the exact upstream revision and bytes before conversion, restores verified
upstream metadata after conversion, and writes complete machine-readable
provenance to MERERUN_CONVERSION.json.
Conversion tool versions:
mlx-vlm==0.6.5mlx==0.32.0mlx-lm==0.31.3mlx-audio==0.4.4transformers==5.14.1safetensors==0.8.0huggingface-hub==1.24.0| Artifact | Bytes | SHA-256 |
|---|---|---|
model-00001-of-00002.safetensors | 5,351,756,584 | 0d58feed0c98a69c07317b4481aeae5ab2785f12a496ea96ab24c4842808de78 |
model-00002-of-00002.safetensors | 1,389,282,927 | 5b00a1bcb596ce6e827b4cdea6ecf2a0f35bb01306eb87c1ea4b3bcde36c7755 |
These independently produced weight shards are byte-identical to the current
mlx-community/gemma-4-12B-it-4bit shards. Sawfwair publishes the conversion
and provenance so releases can be reproduced and audited from the Google
checkpoint rather than depending on an opaque repackaging step.
The converted artifact passed Mere's two deterministic Gemma 4 continuation cases against a real checkpoint:
This validates the local mere.run request adapter and canonical chat-template
path. It is not a broad quality, safety, speed, or multimodal benchmark.
With MLX-VLM on Apple Silicon:
python -m mlx_vlm.generate \
--model Sawfwair/gemma-4-12B-it-MLX-4bit \
--prompt "Explain why the sky is blue in three sentences." \
--max-tokens 160 \
--temperature 0
To reproduce the validated mere.run acceptance test from the
codex/gemma4-template-update
source branch:
hf download Sawfwair/gemma-4-12B-it-MLX-4bit \
--local-dir ./gemma-4-12B-it-MLX-4bit
swift run mere.run model benchmark tool-continuations \
--model-root ./gemma-4-12B-it-MLX-4bit \
--log-responses \
--json
The upstream model is published by Google DeepMind under Apache License 2.0. This repository redistributes a quantized derivative under the same license. See the Google Gemma 4 12B IT model card for the authoritative upstream attribution, license metadata, use guidance, and limitations.
The conversion tooling and native acceptance benchmark live in
sawfwair/mere-run.