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Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-11 · Source: zhipu_bigmodel_official_reference
Mixed text, image, audio and document workloads that benefit from one model across modalities.
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art result...
glm-4.5v is a Multimodal model from Zhipu AI (GLM) (CN). HotON.ai tracks it at $0.60 per 1M input tokens and $1.80 per 1M output tokens, with a 66K-token context window. Its composite efficiency score is 88/100 at an estimated $0.002 per successful task.
glm-4.5v is tracked at $0.60 per 1M input tokens and $1.80 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $1.50 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
glm-4.5v supports up to a 66K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, glm-4.5v is cheaper than 40% of models on input price and ranks #327 of 537 by overall efficiency.
Yes — gemini-2.5-flash-lite-preview-09-2025 is a lower-cost option at $0.40 per 1M output tokens, while still covering similar Multimodal use cases. Compare them side by side on HotON.ai.
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HotON.ai — glm-4.5v (Zhipu AI (GLM)): $0.60/1M input, $1.80/1M output, as of 2026-05-11. https://hoton.ai/en/models/z-ai-glm-4-5vPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.