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
Related
- Base model:
Qwen/Qwen3-VL-235B-A22B-Instruct
𝚅𝚒𝚋𝚎𝚌𝚛𝚊𝚏𝚝𝚎𝚍. with AI Agents by VetCoders (c)2024-2026 LibraxisAI
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Model size
45B params
Tensor type
U8
·
U32 ·
BF16 ·
Hardware compatibility
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4-bit
Model tree for LibraxisAI/Qwen3-VL-235B-A22B-Instruct-mlx-mxfp4
Base model
Qwen/Qwen3-VL-235B-A22B-Instruct