GLM 4.6V
GLM 4.6V is a vision-language model from Z AI featuring native multimodal function calling, interleaved image-text generation, and document understanding.
Model Overview
Capabilities, design details, and architectural traits
GLM 4.6V - Native Multimodal Function Calling Vision-Language Model
GLM 4.6V is Z.AI's (Zhipu AI) open-source vision-language model that introduces native multimodal function calling - bridging the gap between visual perception and executable action to provide a unified foundation for multimodal agents.
Native Multimodal Function Calling
GLM 4.6V's defining capability is its closed-loop perception-to-execution pipeline:
- Multimodal Tool Input: Images, screenshots, and document pages are passed directly as tool call parameters - no prior text conversion required, preventing information loss.
- Multimodal Tool Output: Visual results returned by tools (charts, rendered web screenshots, search-retrieved product images) are directly interpreted and incorporated into subsequent reasoning chains without text intermediaries.
Documented Capabilities
- Interleaved Image-Text Generation: Takes multimodal context (documents, user inputs, tool-retrieved images) and synthesizes coherent, visually grounded mixed-media outputs. During generation, the model can autonomously call search and retrieval tools to curate additional visuals.
- Multimodal Document Understanding: Processes up to 128K tokens of multi-document input as direct image pages - interpreting text, layout, charts, tables, and figures jointly without OCR preprocessing. Equivalent to ~150 complex document pages, 200 slide pages, or a 1-hour video in a single inference pass.
- Frontend Replication & Visual Editing: Reconstructs pixel-accurate HTML/CSS/JS from UI screenshots by detecting layout, components, and color schemes. Supports natural-language-driven iterative visual edits - users can circle a region and issue a text instruction; the model locates and corrects the corresponding code.
Benchmark Performance
Independent evaluations · Artificial Analysis
Accuracy & Capability Details
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| Model Details | |||
|---|---|---|---|
| General Info | |||
| Provider | Z AI | Anthropic | Anthropic |
| Release Date | December 8, 2025 | September 22, 2026 | September 28, 2026 |
| Knowledge Cutoff | - | - | Jun 2026 |
| Context & Limits | |||
| Context Window | 131K | 1M Best Context Window | 1M Best Context Window |
| Pricing (per 1M tokens) | |||
| Input Pricing | $0.30 Best Input Pricing | $4 | $2 |
| Output Pricing | $0.90 Best Output Pricing | $20 | $10 |
| Modalities | |||
| Inputs | imagetextvideo | textimagefile | textimagefile |
| Outputs | text | text | text |
| Benchmarks (0-100) | |||
| Intelligence Index | 8.4 | 57.6 Best Intelligence Index | 56.0 |
| Coding Index | - | - | - |
| Agentic Index | - | - | - |
Humanity's Last Exam
Extremely difficult logical reasoning and knowledge.
Long Context Reasoning
Logical reasoning over long context windows.
SciCode Benchmark
Scientific coding and mathematical modeling.
Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.
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