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, image Q&A, OCR, and document parsing, with strong gains in front-end web coding, grounding, and spatial reasoning. It offers a hybrid inference mode: a "thinking mode" for deep reasoning and a "non-thinking mode" for fast responses. Reasoning behavior can be toggled via the reasoning enabled boolean. Learn more in our docs(opens in new tab)
Modalities
In / Out Price
$0.60 / $1.80per 1M
Context
66K
Released
Aug 11, 2025
Knowledge Cutoff
Dec 2024
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows where this model lands among all models on OpenRouter.
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Token volume and request traffic to this model over time.
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
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, image Q&A, OCR, and document parsing, with strong gains in front-end web coding, grounding, and spatial reasoning.
GLM 4.5V costs $0.60/M input tokens and $1.80/M output tokens, with separate rates for Cache Read at $0.11/M tokens.
GLM 4.5V has a 65,536 token context window. It supports up to 16,384 completion tokens.
Yes. GLM 4.5V accepts tools and tool_choice for function calling. It supports response_format for JSON output, without JSON-schema enforcement.
GLM 4.5V accepts text and images as input and returns text.
GLM 4.5V is served by 2 providers on OpenRouter: NovitaAI and Z.ai. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
GLM 4.5V was released on August 11, 2025. Its knowledge cutoff is December 31, 2024.
| $0.60 | $1.80 | $0.11 | 3.70s | 35 tps | ||
| $0.60 | $1.80 | $0.11 | 2.01s | 64 tps |
Throughput
64tok/s
P50, best across providers
Latency
2.01s
P50, best provider
100.00%
99.97%
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.