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DataBubble·

Model Detail

zai-org logo

GLM-OCR

▼ 1.5%
Provider: zai-orgCategory: multimodalPipeline: image-text-to-text
DB Score
4.1
Downloads
3.4M
Likes
2K
Day
-1.5%
Week
+13.2%
Month
+0.0%
Overview

GLM-OCR is a multimodal model with 663M parameters released by zai-org. The model is registered under the image-text-to-text pipeline tag on Hugging Face, distributed under the permissive mit license.

Technical

GLM-OCR ships with 663M parameters. Total weight footprint is approximately 1.3 GB, which is the relevant figure when planning local-inference VRAM. The mit license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.

Trending Signal

Downloads of GLM-OCR have moved -1.5% over the past 24 hours, +13.2% over the trailing seven days. The trend is mildly positive, consistent with a model that is being picked up incrementally rather than going viral. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.

Read about databubble_score →
Use Cases

GLM-OCR is best fit for mixed text-and-image reasoning tasks such as document understanding. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

Download History
Research Paper
arXiv: 2603.10910→
Model Info
Licensemit
Citations1,623 (173 influential)
Recent newsView all news →
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