This repository contains exactly one MLX variant: the unquantized FP16 SnowFox model. It is a genuine MLX safetensors package, not a GGUF file or a renamed Hugging Face BF16 checkpoint. Four safetensors files make up one model; the shard split is only for reliable large-file download.

SnowFox is a language-only LoRA merge based on Google's Gemma 4 E2B instruction QAT-derived checkpoint. The image and audio towers were frozen during fine-tuning and are retained here, together with the processor and tokenizer needed by MLX-VLM.

Exact lineage

Base: google/gemma-4-E2B-it-qat-q4_0-unquantized
Pinned base revision: 6befbaca7398925921802abd1f277b495b78b738
Canonical merged BF16 source SHA-256: b8fac0ad2cafcb0e7fe29ca6c1deda1389c645751599fe716d4b6f6c0387a2d5
Conversion: structurally converted to the MLX-VLM v0.6.13 Gemma 4 tensor contract, then cast from BF16 to FP16 for storage.
Claim boundary: QAT-derived from the base; SnowFox was not trained in FP16 and the post-LoRA weights were not newly QAT-calibrated.

Package contents

model-00001-of-00004.safetensors through model-00004-of-00004.safetensors: the one FP16 MLX model.
model.safetensors.index.json: complete shard map.
config.json, generation_config.json, processor_config.json, tokenizer files, and chat_template.jinja: Gemma 4 E2B multimodal support files.
mlx_export_manifest.json: source/output provenance and artifact hashes.

Verification performed

The Windows conversion host does not have a compatible MLX runtime, but the stored model conversion was exhaustively verified before upload:

1,951 source tensors mapped to 1,951 MLX tensors with no missing or extra keys.
All 5,104,298,467 stored values were checked after conversion.
Every output tensor is finite FP16, has exact BF16-to-FP16 values, and its safetensors shard declares format=mlx.
The largest absolute stored weight is 900.0, below FP16's finite limit.
The full image/audio/projector tensor set is present; Gemma 4 audio convolution weights use the MLX-VLM axis layout.

Apple-Silicon MLX-VLM inference has not been run from this Windows/AMD release host. Treat this as structurally validated conversion data pending a real Apple-Silicon text, image, and audio generation smoke test; do not interpret the SnowFox training validation scores as fresh MLX runtime results.

Run on Apple Silicon

Use full MLX-VLM, not text-only MLX-LM, because Gemma 4 E2B includes image and audio components:

bash

python -m pip install "mlx-vlm==0.6.13"

python -m mlx_vlm.generate \
  --model MichaelAnthony/gemma4-e2b-Snowfox-MLX \
  --max-tokens 128 \
  --temperature 0.0 \
  --prompt "Explain what SnowFox is in one sentence."

For image prompting, add --image /path/to/image.png to the generation command. Use current MLX-VLM documentation for image, audio, video, and chat-template options.

Quantized variants

Standard MLX-VLM affine quantizations of SnowFox are published as separate repositories and are loadable directly by mlx_vlm.generate:

Variant	Quantization	Size	Notes
`gemma4-e2b-Snowfox-MLX-4bit`	4-bit affine, group 64	~3.55 GB	GGUF `Q4_K_M` analogue
`gemma4-e2b-Snowfox-MLX-6bit`	6-bit affine, group 64	~4.71 GB	GGUF `Q6_K` analogue

These quantize the language backbone (including the large per-layer embeddings) to 4-bit/6-bit affine while keeping the vision and audio towers dense in FP16, so they are smaller than a standard Linear-only quantization.

The earlier oMLX oQ ("oQ4/oQ6/oQ8") build-to-order plan was never published; use the standard 4-bit/6-bit packages above instead.

License

Gemma 4 is Apache-2.0. This derivative package uses the Apache-2.0 license declared by the pinned base model. See LICENSE and NOTICE.md for the lineage and modification notice.