GLM OCR is a language model from Zai Org. It does not hold a position on ModelCap's current board. Its weights are openly downloadable.
Figures as of 6 Nov 2026, 20:49 UTC · download the public dataset · methodology
OpenRouter endpoint status could not be refreshed. This model is not treated as currently served until a successful observation arrives.
Providers
Uptime measured over the last 30 minutesCurrent provider status is unavailable.
Reported evaluation leads (43)
Not independent measurementStructured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.
Showing 20 of 43 rows.
ModelCap Index · Current board
Methodology- Score range
- 23.0–83.9
Technical details
- Public rank basis
- Modeled · prior (architecture)
- Evidence label
- Modeled · prior · global-corpus-prior over 210 held-out anchors (100%)
- Index support
- 4.4% · weak
- Identity binding
- Exact catalogue product · zai-org/zai-org/GLM-OCR · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata zai-org/GLM-OCR@2e85a62840ccac27daa451df36c736c4636b8628 (not the evaluation revision)
- Index observations used
- 0
- Qualified Index evidence point
- 53.5
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
- Fused estimate
- 53.5 ± 23.8
- Independent share
- 0%
- Shrink toward corpus
- 0.0
- Optimism haircut
- None applied
- Method
- precision-weighted-v1
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
- Observed capability
- —
- Evidence status
- No admitted measured evidence
- General preference
- —
- Coding
- —
- Agents & tools
- —
- Reasoning
- —
- Evidence breadth
- 0%
- Evidence coverage
- 0%
- Usage (OpenRouter popularity)
- —
- Liquidity (providers × uptime)
- —
- Open reach (HF downloads)
- 98.4
- Surface (context / tools / modalities)
- 15.0
- Freshness
- 34.3
- · HF 30d downloads 1740322
- · Catalogue: modalities Text/Image
- · First seen 2026-01-30
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Experimental capability estimate
Estimate policy- Confidence
- 71%
- Training support
- 221 models · 129 lineages
- Out-of-domain check
- in domain
- Feature coverage
- 71%
- Lineage-held-out error
- 8.3 MAE
Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Deployment readiness
Metadata index- Artifact reproducibility
- 85.0
- Access & legal clarity
- 100.0
- Deployability
- 8.0
- Evaluation provenance
- 0.0
Not yet published: the base model it derives from, a current serving provider, measured provider uptime, published provider pricing, declared context and output limits, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market activity
Venue coverage- Market Gravity
- 16.5
- OpenRouter weekly popularity
- Not listed
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
Arena preference
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
Market Gravity breakdown
- Usage55%
- 0.0
- Liquidity25%
- 0.0
- Open reach15%
- 98.4
- Freshness5%
- 34.3
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
Specification
- Model ID
zai-org/GLM-OCR- Declared output cap
- Unknown
OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
- Inputs
- Text, Image
- Outputs
- Text
- Cached input tokens
- Not offered
- First seen on OpenRouter
- 30 Jan 2026
Capabilities
- Not supported: Reasoning
- Not supported: Tool use
- Not supported: Structured output
- Not supported: Response format
- Not supported: Moderated
Weights & access
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
- Access
- Open weights
- Licence
- mit
- Pinned revision
- 2e85a62840cc
- Parameters
- 1.3B
- Architecture
- GlmOcrForConditionalGeneration
- Model type
- glm_ocr
- Hugging Face downloads (30d)
- 1.7M
- Downloads (all time)
- 34.3M
- Likes
- 2K
- Repository
- zai-org/GLM-OCR
- Repository updated
- 11 Sept 2026, 11:59 UTC