Z.ai: GLM 4.5V Rank
GLM 4.5V has an overall score of 54 out of 100, tied for rank 250 of 291. The published scores are price 62, context 36, parameters 51, and freshness 68. The overall score is their average. recency is not published and is left out of the average.
Data sourced from OpenRouter API and manual data collection | Last updated: Nov 3, 2026, 8:01 AM UTC
Component scores are ranked in
tied for rank 250 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | 68 | AI Knowledge Cutoff | |
| Recency | — | — | AI Release Date |
| Context | 36 | 65.5K tokens, output 16.4K | AI Context Window |
| Parameters | 51 | 106B total | AI Parameter Count |
| Price | 62 | $0.9 / 1M blended, $0.6 / 1M input, $1.8 / 1M output | AI Token Price |
249 listed models have a higher overall score. Among Z.ai models, it ranks 16 of 16.
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 results in video understanding,...
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Frequently asked questions
What is the GLM 4.5V rank?
GLM 4.5V has an overall score of 54 out of 100, tied for rank 250 of 291. The published scores are price 62, context 36, parameters 51, and freshness 68. The overall score is their average. recency is not published and is left out of the average.
Where does GLM 4.5V rank?
GLM 4.5V is tied for rank 250 of 291. 249 listed models have a higher overall score. Among Z.ai models, it ranks 16 of 16.
What scores make up GLM 4.5V?
GLM 4.5V scores price 62 (AI Token Price), context 36 (AI Context Window), parameters 51 (AI Parameter Count), and freshness 68 (AI Knowledge Cutoff). The overall score of 54 is the average of those 4.