# Z.AI: GLM 4.6V FlashX

z-ai/glm-4.6v-flash

GLM-4.6V-FlashX is the paid version, offering higher capacity and stability, representing a significant iteration in the GLM series for multimodal capabilities. It supports toggling reasoning modes, with a training-time context window expanded to 128k tokens. Achieving state-of-the-art (SOTA) visual understanding accuracy at its parameter scale, it is the first visual model to natively integrate Function Call capability into its architecture. This establishes a seamless pipeline from "visual perception" to "executable actions (Action)", offering a unified technical foundation for multimodal agents in real-world business scenarios.

## Recent activity on GLM 4.6V FlashX

### Tokens processed per day

### Throughput

| Providers | Min (tokens/s) | Max (tokens/s) | Avg (tokens/s) |
| --- | --- | --- | --- |
| BigModel | 20.21 | 78.5 | 47.91 |
| Z.ai | 56.02 | 56.02 | 56.02 |

### First Token Latency

| Providers | Min (ms) | Max (ms) | Avg (ms) |
| --- | --- | --- | --- |
| BigModel | 797 | 9489 | 2019.14 |
| Z.ai | 31734 | 31734 | 31734.00 |

### Uptime stats for GLM 4.6V FlashX

Uptime stats for GLM 4.6V FlashX across all providers

| Providers | Uptime (%) |
| --- | --- |
| BigModel | 100.00 |
| Z.AI | - |

## Pricing

### Tiered Pricing

| Input Size | Fee |
| --- | --- |
| 0 ≤ Input < 32k | $0.0218/M tokens |
| Output | $0.2184/M tokens |
| Cache read | $0.0044/M tokens |
| Web search | $0.01/counts |

### Model Limitations

- Context: 200.00K
- Max output: 128.00K

## Sample code and API for GLM 4.6V FlashX

ZenMux normalizes requests and responses across providers for you.

```python
from openai import OpenAI

client = OpenAI(
  base_url="https://zenmux.ai/api/v1",
  api_key="<ZENMUX_API_KEY>",
)

# Chat Completion
completion = client.chat.completions.create(
  model="z-ai/glm-4.6v-flash",
  messages=[
    {
      "role": "user",
      "content": "What is the meaning of life?"
    }
  ]
)
print(completion.choices[0].message.content)
```