GLM 4.6V
Z.ai (Zhipu AI)family · GLM4.6
GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...
Updated 4 h ago · first seen 11 Sept 2026
model_01M294WW7QNQ16FETBBDXKYPRV
Overview
Identity
- Canonical model
- Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 2
- API aliases
- glm-4-6vglm-4-6v-reasoningz-ai/glm-4.6vIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 1Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable; 7 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
—
Redistribution
—
Derivatives
—
dimensions marked null are unknown, not false
Key facts
- Release date
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
- Status
Source:Artificial AnalysisT2observed 13 h agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
Architecture
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
Capabilities
Modalities
- Modalities
- imagetextvideo
- Input
- imagetextvideo
- Output
- text
Capabilities
Tool calling
Yes
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
Yes
OpenRouter public model & pricing listing · T2
Vision
Yes
OpenRouter public model & pricing listing · T2
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:OpenRouter public model & pricing listingT2observed 11 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
Benchmarks28
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 28 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →
Providers & Pricing2
All offers in the price terminal →USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →
Price history
Output price · USD / 1M tokens 2 providers
- Z.ai API
- OpenRouter
- OpenRouterfirst observed $0.9012 Sept 2026
- Z.ai APIfirst observed $0.9011 Sept 2026
Input price · USD / 1M tokens 2 providers
- Z.ai API
- OpenRouter
- OpenRouterfirst observed $0.3012 Sept 2026
- Z.ai APIfirst observed $0.3011 Sept 2026
Versions & Artifacts0
Version history
Context window2 changes
11 Sept 2026→11 Sept 2026→12 Sept 2026current
Max outputfirst observation only
11 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Statusfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 0
No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.
Timeline17
Full timeline →OpenRouter lists GLM 4.6V at $0.3 in / $0.9 out per 1M tokens
openrouterGLM 4.6V: reasoning changed from false to true
ReasoningNo→YesopenrouterGLM 4.6V scores 3.03% on Terminal-Bench
artificial_analysisGLM 4.6V scores 3.66% on Humanity's Last Exam
artificial_analysisGLM 4.6V scores 56.57% on GPQA Diamond
artificial_analysisGLM 4.6V scores 8.35 on Artificial Analysis Intelligence Index
artificial_analysisGLM 4.6V scores 14.39% on Terminal-Bench
artificial_analysisGLM 4.6V scores 9.64% on Humanity's Last Exam
artificial_analysisGLM 4.6V scores 71.92% on GPQA Diamond
artificial_analysisGLM 4.6V scores 11.22 on Artificial Analysis Intelligence Index
artificial_analysisGLM 4.6V: context length changed from 128000 to 131072
Context window128K tokens→131.1K tokensopenrouter
Change history
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second2
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
22
Source tiers
T222
Freshest observation
4 h ago
Conflicts
None
Source documents 2
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (60/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →