GLM 4.5V
glm-4.5vGLM-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,... Built by Z.ai.
Prices updated
Input price
$0.60
per 1M tokens · Standard
Output price
$1.80
per 1M tokens · Standard
Input limit
66K
tokens
Output limit
16K
tokens
Input formats
Output formats
GLM 4.5V price history
2 price records since 9/25/2026
GLM 4.5V cost calculator
$21/month
Standard pricing
Overview
What is GLM 4.5V?
GLM 4.5V is a text & reasoning and vision model from Z.ai. 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,... Its 66K context window and $0.60 input price make it a candidate for quality-focused production applications.
Benchmarks
GLM 4.5V benchmarks & speed
How GLM 4.5V scores on standardized evaluations, and where it lands among every model we track.
6.7
Intelligence Index
53tok/s
Output speed
Reasoning
GPQA Diamond
57.3%
Graduate-level scientific reasoning · top 82%
HLE
3.5%
Humanity's Last Exam · top 95%
Latency & design
- Time to first token
- 2.73s
Independent scores from Artificial Analysis and DesignArena · updated 10/5/2026. Higher is better; ranks compare against every model we track with that score.
Rates
GLM 4.5V pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.60
Per 1M tokens
Cached input · Standard
$0.11
Per 1M tokens
Capabilities
GLM 4.5V Tools
Tools available when using GLM 4.5V through supported provider APIs.
Function calling
Supported
Structured outputs
Not supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Not supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Measured results (AA Intelligence 6.7) position it for demanding production work.
- A 66K context window covers most focused application workflows.
- Supports text & reasoning and vision workloads in one model.
Limitations
- Generated tokens cost 3× more than input tokens, which matters for verbose responses.
- The 66K context window is smaller than several long-context alternatives.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider