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

Parameter Value
Repository LibraxisAI/Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4
Base model Qwen/Qwen3-VL-235B-A22B-Instruct
Task image-text-to-text
Library mlx
Format MLX / Apple Silicon checkpoint
Quantization MXFP4
Architecture Qwen3VLMoeForConditionalGeneration
Model files 24
Config model_type qwen3_vl_moe

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.

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. Run the usage example above against your own prompt or audio/image input to inspect behavior.

Quantization notes

Aspect Original/base checkpoint This checkpoint
Lineage Qwen/Qwen3-VL-235B-A22B-Instruct LibraxisAI/Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4
Runtime target Upstream runtime format MLX on Apple Silicon
Quantization Base precision or upstream-declared format MXFP4
Published quality delta Not declared in public metadata Not declared in public metadata

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}
}

Inference tested on

LibraxisAI/mlx-batch-server

Related


𝚅𝚒𝚋𝚎𝚌𝚛𝚊𝚏𝚝𝚎𝚍. with AI Agents by VetCoders (c)2024-2026 LibraxisAI

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