Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4

Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4

Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4 is an MLX vision-language checkpoint derived from Qwen/Qwen3-VL-235B-A22B-Instruct, packaged for local multimodal prompting on Apple Silicon.

Intended use

• Local image-and-text reasoning on Apple Silicon
• Document, screenshot, chart, and visual question answering experiments
• Operator-controlled multimodal prototyping where hosted inference is not desired

Out of scope

• Safety-critical decisions without domain expert review
• Claims of benchmark superiority not backed by published evaluation data
• Non-MLX runtime guarantees; this card documents the shipped HF checkpoint, not every possible serving stack
• High-stakes visual interpretation without human review

Training and conversion metadata

This card only reports metadata present in the Hugging Face repository, existing card frontmatter, or public config files. Missing benchmark, dataset, or training-run details are left explicit rather than reconstructed.

Tested inference path

Inference for this checkpoint has been tested with LibraxisAI/mlx-batch-server.
This is the recommended tested path for operator-controlled local inference on Apple Silicon.

This does not claim compatibility with every possible serving stack. It documents the path that has been exercised for this published checkpoint.

Usage

CLI

pip install mlx-vlm

python -m mlx_vlm.generate \
  --model LibraxisAI/Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4 \
  --image image.jpg \
  --prompt "Summarize the key signals in this document and list the next action items." \
  --max-tokens 256

Python

from mlx_vlm import generate, load

model, processor = load("LibraxisAI/Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4")
response = generate(
    model,
    processor,
    prompt="Summarize the key signals in this document and list the next action items.",
    image="image.jpg",
    max_tokens=256,
)
print(response)

Example output

No public sample output is currently declared for this checkpoint.

Quantization notes

Limitations

• No public benchmarks for this checkpoint are declared in the model metadata.
• No public benchmark claims are made by this card unless listed in the frontmatter.
• Validate outputs on your own domain data before relying on this checkpoint.
• Memory use and speed depend heavily on the exact Apple Silicon generation, unified-memory size, and prompt length.

License

apache-2.0. Check the upstream/base model license as well when a base model is declared.

Citation

@misc{libraxisai-qwen3-vl-235b-a22b-instruct-mlx-mxfp4,
  title = {Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4},
  author = {LibraxisAI},
  year = {2026},
  howpublished = {\url{https://huggingface.co/LibraxisAI/Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4}},
  note = {MLX checkpoint published by LibraxisAI}
}

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