Hugging Face model card
Fields: tags, gated, license, summary, languages, library name, pipeline tag
This model is part of the GLM-V family of models, introduced in the paper GLM-4.1V-Thinking and GLM-4.5V: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.
- Context
- 131K
- Max output
- 33K
- Input
- $0.30
- Output
- $0.90
Recommended use cases
Strengths in this dataset
- 131,072-token context window
- image, text, video input
- 14 supported API parameters listed
Limits and caveats
- Provider behavior and pricing can change; verify the linked sources before production use.
Capability
Model-native facts
Model- Reasoning
- Supported
- Open weights
- Unknown
Provider endpoint facts
Provider endpoint- Tool calling
- Supported
- Structured output
- Supported
- Streaming
- Unknown
- Prompt cache
- Supported
- Batch
- Unknown
- Fine-tuning
- Unknown
GLM 4.6V Provider pricing
Provider endpoint: z-ai/glm-4.6v
- Input
- $0.30 per 1M tokens
- Output
- $0.90 per 1M tokens
- Cached input
- $0.055 per 1M tokens
- Image output
- Unknown per 1M tokens
Sources and verification
Official model documentation
Fields: model identity
OpenRouter Models API
Fields: identity, description, modalities, context window, maximum output, pricing, supported parameters
Frequently asked questions
Answers are generated from the same sourced model and provider facts shown above.
This model is part of the GLM-V family of models, introduced in the paper GLM-4.1V-Thinking and GLM-4.5V: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.
Model specifications and prices may vary by provider and change over time. AIToolly displays sources and verification dates so users can confirm critical details before production use.