🧠
Model

Glm Ocr 4bit G32 Mxfp4 Mixed 4 8 Mlx

by EZCon hf-model--ezcon--glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx
Nexus Index
43.3 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 30
R: Recency 98
Q: Quality 65
Tech Context
4 Params
4.096K Ctx
Vital Performance
1.6K DL / 30D
0.0%
Audited 43.3 FNI Score
4B Params
4k Context
1.6K Downloads
8G GPU ~5GB Est. VRAM
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--ezcon--glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx
License MIT
Provider huggingface
💾

Compute Threshold

~4.3GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{hf_model__ezcon__glm_ocr_4bit_g32_mxfp4_mixed_4_8_mlx,
  author = {EZCon},
  title = {Glm Ocr 4bit G32 Mxfp4 Mixed 4 8 Mlx Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ezcon/glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
EZCon. (2026). Glm Ocr 4bit G32 Mxfp4 Mixed 4 8 Mlx [Model]. Free2AITools. https://huggingface.co/ezcon/glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx
🤗 HF Download
huggingface-cli download ezcon/glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx
đŸ“Ļ Install Lib
pip install -U transformers

âš–ī¸ Nexus Index V2.0

43.3
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 30
Recency (R) 98
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Glm Ocr 4bit G32 Mxfp4 Mixed 4 8 Mlx: Semantic (S:50), Authority (A:0), Popularity (P:30), Recency (R:98), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

Technical Deep Dive

EZCon/GLM-OCR-4bit-g32-mxfp4-mixed_4_8-mlx

This model was converted to MLX format from zai-org/GLM-OCR using mlx-vlm version 0.4.4. Refer to the original model card for more details on the model.

Use with mlx

bash
pip install -U mlx-vlm
bash
python -m mlx_vlm.generate --model EZCon/GLM-OCR-4bit-g32-mxfp4-mixed_4_8-mlx --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image 

âš ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
1.6KDownloads
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseâ„šī¸ Verify with original source

đŸ›Ąī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--ezcon--glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx
slug
ezcon--glm-ocr-4bit-g32-mxfp4-mixed_4_8-mlx
source
huggingface
author
EZCon
license
MIT
tags
transformers, safetensors, glm_ocr, image-text-to-text, mlx, image-to-text, zh, en, fr, es, ru, de, ja, ko, base_model:zai-org/glm-ocr, base_model:quantized:zai-org/glm-ocr, license:mit, endpoints_compatible, 4-bit, region:us, base_model:unsloth/glm-ocr, base_model:quantized:unsloth/glm-ocr, conversational

âš™ī¸ Technical Specs

architecture
null
params billions
4
context length
4,096
pipeline tag
image-text-to-text
vram gb
4.3
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
1,633
stars
0
forks
null

Data indexed from public sources. Updated daily.