GLM-4V-9B is an open-source multimodal language model with visual understanding capabilities, built by Z.ai. It excels at Chinese and English bilingual multi-turn dialogue at high resolutions (1120x1120) and performs well across a range of multimodal evaluations.
Input
Output
Context
8K
Max Output
8K
Parameters
13.9B
Input Modalities
Output Modalities
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Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
The creator's other models in the catalog, with their context, size and license where published.
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Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Glm 4v 9B advertises a context window of 8,192 tokens, with a maximum output of 8,192 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Glm 4v 9B is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Glm 4v 9B accepts Text and Image and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Glm 4v 9B is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Glm 4v 9B is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 14.0 GB at INT8 for the weights and a default context, from the catalog's 13.9B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
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