GLM 5

Developer documentation

GLM 5

GLM 5 through Google Vertex AI Model Garden/MaaS with Omixa routing and streaming.

Model Reference

Chat and reasoning models

Language, code, reasoning, multimodal chat, tool calling, and streaming responses. Endpoint: http://omixa.cloud/api/v1/chat/completions

GLM 5

glm-5

GLM 5 through Google Vertex AI Model Garden/MaaS with Omixa routing and streaming.

Chat Streaming Tools Context window: 200,000 tokens Max output: 128,000 tokens
input per 1m tokens $1.000000
cached input per 1m tokens $0.100000
output per 1m tokens $3.200000
Integration reference

Connect GLM 5

Use Omixa's unified endpoint and your workspace API key. Provider routing, billing, failover, and usage records are handled by Omixa.

POST http://omixa.cloud/api/v1/chat/completions
  • Provider: google
  • Endpoint type: google_openai_chat
  • Context window: 200,000 tokens
  • Max output: 128,000 tokens
  • Streaming supported
  • Tool/function calling supported
  • Reasoning controls: none, low
Request schema

Request fields

Only send options supported by this model. Required fields and accepted values are listed below.

Field Type Required Accepted values Description
model string Yes glm-5 Use `glm-5`. Omixa resolves the active provider route and failover key automatically.
messages array Yes Any valid value Conversation turns. Each item contains `role` and `content`. Roles are `system`, `user`, `assistant`, and tool roles when supported.
messages[].content string|array Yes Any valid value Text prompt or multimodal parts. Multimodal-capable models accept `{type:"text"}`, `{type:"image_url"}`, and inline files supported by Omixa.
stream boolean No Any valid value When true, returns OpenAI-compatible Server-Sent Events until `data: [DONE]`.
max_tokens|max_completion_tokens integer No Any valid value Maximum answer tokens. Omixa maps the correct field for Google, Azure chat, and reasoning model families.
temperature number No Any valid value Sampling randomness for non-reasoning models. Reasoning-only models may ignore or reject it, so Omixa strips it where needed.
top_p number No Any valid value Nucleus sampling. Use either `temperature` or `top_p` for predictable tuning.
stop string|array No Any valid value Stop sequence or sequences. Not all provider routes support it.
response_format object No Any valid value Structured output hints such as `{ "type": "json_object" }` when the selected provider supports JSON mode.
tools array No Any valid value OpenAI-style tool/function declarations. Omixa forwards compatible declarations to tool-capable providers.
tool_choice string|object No Any valid value `auto`, `none`, `required`, or a specific tool choice when the provider supports it.
reasoning_effort string No none, low Reasoning budget/effort. Omixa normalizes options per provider family.
show_thinking boolean No Any valid value Requests reasoning summaries or native `reasoning_content` chunks when supported by the selected route.
Ready to send

Payload and response

Start with this model-safe payload and expect the normalized Omixa response shape shown beside it.

Example JSON payload
{
    "model": "glm-5",
    "messages": [
        {
            "role": "system",
            "content": "You are a concise API assistant."
        },
        {
            "role": "user",
            "content": "Explain this model in three practical bullet points."
        }
    ],
    "stream": true,
    "max_tokens": 2048,
    "reasoning_effort": "none",
    "show_thinking": true,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "lookup_order",
                "description": "Return order status by ID.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string"
                        }
                    },
                    "required": [
                        "order_id"
                    ]
                }
            }
        }
    ],
    "tool_choice": "auto"
}
Response shape
{
    "object": "chat.completion",
    "choices": [
        {
            "message": {
                "role": "assistant",
                "content": "..."
            }
        }
    ],
    "usage": {
        "prompt_tokens": 123,
        "completion_tokens": 45,
        "total_tokens": 168
    }
}
Language examples

Copy-ready integration code

Replace the example API key with a workspace key and keep model-specific fields unchanged unless the table above marks them optional.

cURL
curl -X POST http://omixa.cloud/api/v1/chat/completions \
  -H "Authorization: Bearer omx_live_xxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5",
    "messages": [
        {
            "role": "system",
            "content": "You are a concise API assistant."
        },
        {
            "role": "user",
            "content": "Explain this model in three practical bullet points."
        }
    ],
    "stream": true,
    "max_tokens": 2048,
    "reasoning_effort": "none",
    "show_thinking": true,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "lookup_order",
                "description": "Return order status by ID.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string"
                        }
                    },
                    "required": [
                        "order_id"
                    ]
                }
            }
        }
    ],
    "tool_choice": "auto"
}'
JavaScript fetch
const response = await fetch('http://omixa.cloud/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer omx_live_xxx',
    'Content-Type': 'application/json'
  },
  body: "{\n    \"model\": \"glm-5\",\n    \"messages\": [\n        {\n            \"role\": \"system\",\n            \"content\": \"You are a concise API assistant.\"\n        },\n        {\n            \"role\": \"user\",\n            \"content\": \"Explain this model in three practical bullet points.\"\n        }\n    ],\n    \"stream\": true,\n    \"max_tokens\": 2048,\n    \"reasoning_effort\": \"none\",\n    \"show_thinking\": true,\n    \"tools\": [\n        {\n            \"type\": \"function\",\n            \"function\": {\n                \"name\": \"lookup_order\",\n                \"description\": \"Return order status by ID.\",\n                \"parameters\": {\n                    \"type\": \"object\",\n                    \"properties\": {\n                        \"order_id\": {\n                            \"type\": \"string\"\n                        }\n                    },\n                    \"required\": [\n                        \"order_id\"\n                    ]\n                }\n            }\n        }\n    ],\n    \"tool_choice\": \"auto\"\n}"
});
const data = await response.json();
Python requests
import requests

response = requests.post(
    'http://omixa.cloud/api/v1/chat/completions',
    headers={'Authorization': 'Bearer omx_live_xxx', 'Content-Type': 'application/json'},
    json={
    "model": "glm-5",
    "messages": [
        {
            "role": "system",
            "content": "You are a concise API assistant."
        },
        {
            "role": "user",
            "content": "Explain this model in three practical bullet points."
        }
    ],
    "stream": True,
    "max_tokens": 2048,
    "reasoning_effort": "none",
    "show_thinking": True,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "lookup_order",
                "description": "Return order status by ID.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string"
                        }
                    },
                    "required": [
                        "order_id"
                    ]
                }
            }
        }
    ],
    "tool_choice": "auto"
}
)
print(response.json())
PHP cURL
$ch = curl_init('http://omixa.cloud/api/v1/chat/completions');
curl_setopt_array($ch, [
    CURLOPT_POST => true,
    CURLOPT_HTTPHEADER => ['Authorization: Bearer omx_live_xxx', 'Content-Type: application/json'],
    CURLOPT_POSTFIELDS => '{
    "model": "glm-5",
    "messages": [
        {
            "role": "system",
            "content": "You are a concise API assistant."
        },
        {
            "role": "user",
            "content": "Explain this model in three practical bullet points."
        }
    ],
    "stream": true,
    "max_tokens": 2048,
    "reasoning_effort": "none",
    "show_thinking": true,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "lookup_order",
                "description": "Return order status by ID.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string"
                        }
                    },
                    "required": [
                        "order_id"
                    ]
                }
            }
        }
    ],
    "tool_choice": "auto"
}',
    CURLOPT_RETURNTRANSFER => true,
]);
$response = curl_exec($ch);
C# HttpClient
using var client = new HttpClient();
client.DefaultRequestHeaders.Authorization = new System.Net.Http.Headers.AuthenticationHeaderValue("Bearer", "omx_live_xxx");
var json = @"{
    ""model"": ""glm-5"",
    ""messages"": [
        {
            ""role"": ""system"",
            ""content"": ""You are a concise API assistant.""
        },
        {
            ""role"": ""user"",
            ""content"": ""Explain this model in three practical bullet points.""
        }
    ],
    ""stream"": true,
    ""max_tokens"": 2048,
    ""reasoning_effort"": ""none"",
    ""show_thinking"": true,
    ""tools"": [
        {
            ""type"": ""function"",
            ""function"": {
                ""name"": ""lookup_order"",
                ""description"": ""Return order status by ID."",
                ""parameters"": {
                    ""type"": ""object"",
                    ""properties"": {
                        ""order_id"": {
                            ""type"": ""string""
                        }
                    },
                    ""required"": [
                        ""order_id""
                    ]
                }
            }
        }
    ],
    ""tool_choice"": ""auto""
}";
var response = await client.PostAsync("http://omixa.cloud/api/v1/chat/completions", new StringContent(json, System.Text.Encoding.UTF8, "application/json"));
var body = await response.Content.ReadAsStringAsync();
Go net/http
payload := []byte(`{
    "model": "glm-5",
    "messages": [
        {
            "role": "system",
            "content": "You are a concise API assistant."
        },
        {
            "role": "user",
            "content": "Explain this model in three practical bullet points."
        }
    ],
    "stream": true,
    "max_tokens": 2048,
    "reasoning_effort": "none",
    "show_thinking": true,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "lookup_order",
                "description": "Return order status by ID.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string"
                        }
                    },
                    "required": [
                        "order_id"
                    ]
                }
            }
        }
    ],
    "tool_choice": "auto"
}`)
req, _ := http.NewRequest("POST", "http://omixa.cloud/api/v1/chat/completions", bytes.NewReader(payload))
req.Header.Set("Authorization", "Bearer omx_live_xxx")
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
Streaming note
Set `"stream": true` and read Server-Sent Events line by line until `data: [DONE]`. Each event is OpenAI-compatible `chat.completion.chunk` JSON.
Production checklist

Operational notes

  • Authenticate with `Authorization: Bearer omx_live_xxx`.
  • Omixa handles provider keys, routing, billing, failover, and usage recording behind this endpoint.
  • Google Vertex requests use active Vertex accounts configured by the admin; Omixa retries the next healthy account when a route fails before output starts.
  • This model is routed through Vertex OpenAI-compatible chat. Omixa normalizes native reasoning chunks and provider-specific controls.
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