Huihui4-48B-A4B-vmlx-fp16
Huihui4-48B-A4B-vmlx-fp16 is an MLX vision-language checkpoint derived from huihui-ai/Huihui4-48B-A4B-abliterated, 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/Huihui4-48B-A4B-vmlx-fp16 |
| Base model | huihui-ai/Huihui4-48B-A4B-abliterated |
| Task | image-text-to-text |
| Library | mlx |
| Format | MLX / Apple Silicon checkpoint |
| Quantization | BF16/FP16 |
| Architecture | Gemma4ForConditionalGeneration |
| Model files | 19 |
| Config model_type | gemma4 |
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/Huihui4-48B-A4B-vmlx-fp16 \
--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/Huihui4-48B-A4B-vmlx-fp16")
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 | huihui-ai/Huihui4-48B-A4B-abliterated |
LibraxisAI/Huihui4-48B-A4B-vmlx-fp16 |
| Runtime target | Upstream runtime format | MLX on Apple Silicon |
| Quantization | Base precision or upstream-declared format | BF16/FP16 |
| 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-huihui4-48b-a4b-vmlx-fp16,
title = {Huihui4-48B-A4B-vmlx-fp16},
author = {LibraxisAI},
year = {2026},
howpublished = {\url{https://huggingface.co/LibraxisAI/Huihui4-48B-A4B-vmlx-fp16}},
note = {MLX checkpoint published by LibraxisAI}
}
Inference tested on
Related
- Base model:
huihui-ai/Huihui4-48B-A4B-abliterated
𝚅𝚒𝚋𝚎𝚌𝚛𝚊𝚏𝚝𝚎𝚍. with AI Agents by VetCoders (c)2024-2026 LibraxisAI
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- 104
Model size
49B params
Tensor type
BF16
·
Hardware compatibility
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Quantized
Model tree for LibraxisAI/Huihui4-48B-A4B-vmlx-fp16
Base model
google/gemma-4-26B-A4B Finetuned
google/gemma-4-26B-A4B-it Finetuned
unsloth/gemma-4-26B-A4B-it Finetuned
huihui-ai/Huihui4-48B-A4B-abliterated