Flash lightweight variant
According to the model card, GLM-4.6V-Flash is the lightweight model in the GLM-4.6V series, optimized for local deployment and low-latency applications.
Open Source Model Profile · zai-org
GLM-4.6V-Flash is a 10.29B-parameter glm4v vision-language release from zai-org. According to the model card, the Flash variant targets local deployment and low-latency applications.
GLM-4.6V-Flash is published by zai-org as a glm4v image-text-to-text model. The captured configuration identifies Glm4vForConditionalGeneration with model type glm4v, and Safetensors metadata reports 10,292,777,472 parameters. According to the model card, it is the lightweight GLM-4.6V-series variant for local deployment and low-latency use.
According to the model card, GLM-4.6V-Flash is the lightweight model in the GLM-4.6V series, optimized for local deployment and low-latency applications.
Captured configuration identifies Glm4vForConditionalGeneration with model type glm4v, and Safetensors metadata reports 10,292,777,472 parameters.
According to the model card, the series integrates native function calling that uses images, screenshots, and document pages directly as tool inputs.
According to the model card, GLM-4.6V scales its context window to 128K tokens in training, with documented vLLM and SGLang inference settings.
Source: zai-org/GLM-4.6V-Flash
Captured: Unknown. Processed: 2026-09-07T19:35:01.508102+00:00.
GLM-4.6V 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 . GLM-4.6V Blog : https://z.ai/blog/glm-4.6v Paper : https://huggingface.co/papers/2507.01006 GitHub Repository : https://github.com/zai-org/GLM-V Online Demo : https://chat.z.ai/ API Access : Z.ai Open Platform Desktop Assistant App : https://huggingface.co/spaces/zai-org/GLM-4.5V-Demo-App Introduction GLM-4.6V series model includes two versions: GLM-4.6V (106B), a foundation model designed for cloud and high-performance cluster scenarios, and…
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