> ## Documentation Index
> Fetch the complete documentation index at: https://docs.deploy.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Z.AI GLM-5.3-Flash

***

GLM-5.3-Flash is the first natively multimodal model in the GLM-5 series from [Z.ai](http://Z.ai).

***

# **Parameters**

| **Field** | **Type** | **Definition** | **Default Value** |
| :- | :- | :- | :- |
| `model` | str | **Required**. The model key to be used. Use `zai-org/glm-5.3-flash`. | `zai-org/glm-5.3-flash` |
| `messages` | arr | **Required**. Conversation history. Each object has a `role` (`user` or `assistant`) and `content` (str). | - |
| `stream` | bool |  Routes the request to the streaming path vs non-streaming path. | `false` |
| `max_completion_tokens` | int | Output token cap. | - |
| `temperature` | float | Randomness. Greedy sampling at `0` ; identical results are not guaranteed. | `1` |
| `top_p` | float | Nucleus sampling cutoff. | `1` |
| `top_k` | int | Limits sampling to the top K tokens. | - |
| `reasoning_effort` | str | Constrains effort on reasoning for reasoning models. Supported values are `low`, `high`, `max`. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. | `max` |
| `n` | int | How many chat completion choices to generate for each input message. Currently, we only support `1`. | `1` |
| `presence_penalty` | float | Number between `-2.0` and `2.0`. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics. | `0` |
| `frequency_penalty` | float | Number between `-2.0` and `2.0`. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim. | `0` |
| `logprobs` | bool | Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message. | `false` |

***

# Request Format

```python Python theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api-cdn.deploy.com/api/v1",
    api_key="DEPLOY_API_KEY",
)
response = client.chat.completions.create(
    model="zai-org/glm-5.3-flash",
    messages=[{"role": "user", "content": "Explain TCP and UDP in two sentences."}],
)

print(response.choices[0].message.content)
```

```bash cURL theme={null}
curl https://api-cdn.deploy.com/api/v1/chat/completions \
  -H "Authorization: Bearer $DEPLOY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "zai-org/glm-5.3-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
```

# Response Format

```json JSON theme={null}
{
  "id": "chatcmpl-b159b5c8-ccd8-11f1-bb01-70ff0b34584b",
  "object": "chat.completion",
  "created": 1792536648,
  "model": "zai-org/glm-5.3-flash",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! I'm GLM, trained by Z.ai. How can I help you today? Whether you have questions, want to discuss a topic, or need assistance with something, I'm here to chat.",
        "refusal": null,
        "annotations": null,
        "audio": null,
        "function_call": null,
        "reasoning": "Let me consider how to respond to this greeting appropriately.\n\nThe user has initiated the conversation with a simple \"Hello!\" - this is a friendly and open-ended way to start. I should respond in kind, matching their friendly tone while also being welcoming and open to whatever they might want to discuss next.\n\nI'll acknowledge their greeting warmly and let them know I'm ready to help. It would be good to keep the response concise and natural, without overwhelming them with too much information. A simple, friendly response that invites further conversation would be ideal.\n\nThe response should be warm and professional, making it clear I'm here to assist while giving them space to direct the conversation as they wish.\n\nLet me craft a response that's both welcoming and open-ended, without being too formal or overly casual."
      },
      "logprobs": null,
      "finish_reason": "stop",
      "stop_reason": 154827,
      "token_ids": null,
      "routed_experts": null
    }
  ],
  "service_tier": null,
  "system_fingerprint": null,
  "usage": {
    "prompt_tokens": 14,
    "total_tokens": 216,
    "completion_tokens": 202,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "created_cache_tokens": 0,
      "multimodal_tokens": null
    },
    "completion_tokens_details": { "reasoning_tokens": 158 }
  },
  "prompt_logprobs": null,
  "prompt_token_ids": null,
  "prompt_text": null,
  "kv_transfer_params": null,
  "ec_transfer_params": null,
  "metrics": null
}
```


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