GLM-5.3 FlashX

by zai · family glm

Facts

Release date	2026-09-18
Retired date	—
Knowledge cutoff	—
Context (max)	1,048,576
Max output	—
Modalities	text, image, video → text
Aliases	`glm-5.3-flashx`
Open weights	yes
Description	High-speed variant of GLM-5.3-Flash on the same hybrid sparse+linear attention multimodal architecture: up to 200 tokens/s generation for latency-sensitive applications. $0.37/$1.25 per Mtok on OpenRouter; thinking enabled-only like the rest of the GLM-5.3 line.

Unknown values are shown as —.

Offerings

Provider	Wire ID	Variant	Endpoint	Protocol	Status	Price (USD / Mtok)	Reasoning
OpenRouter	`z-ai/glm-5.3-flashx`		chat-completions	openai-chat	ga	0.37 / 1.25	effort · default on · mandatory · returns reasoning_content · round-trips reasoning_content

Reasoning controls

OpenRouter· z-ai/glm-5.3-flashx· chat-completions effort

reasoning.effort lowmedium●highxhighmax

effort · default on · mandatory · returns reasoning_content · round-trips reasoning_content

Example requests

OpenRouter · openai-chat · z-ai/glm-5.3-flashx

curl 'https://openrouter.ai/api/v1/chat/completions' \
  -H 'Authorization: Bearer <YOUR_API_KEY>' \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "z-ai/glm-5.3-flashx",
  "messages": [
    {
      "role": "user",
      "content": "Tell me about the weather."
    }
  ],
  "reasoning": {
    "effort": "medium"
  }
}'

Python (requests)

import requests

resp = requests.post(
    "https://openrouter.ai/api/v1/chat/completions",
    headers={
      "Authorization": "Bearer <YOUR_API_KEY>",
      "Content-Type": "application/json"
    },
    json={
      "model": "z-ai/glm-5.3-flashx",
      "messages": [
        {
          "role": "user",
          "content": "Tell me about the weather."
        }
      ],
      "reasoning": {
        "effort": "medium"
      }
    },
)
print(resp.json())

TypeScript (fetch)

const resp = await fetch("https://openrouter.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": "Bearer <YOUR_API_KEY>",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    "model": "z-ai/glm-5.3-flashx",
    "messages": [
      {
        "role": "user",
        "content": "Tell me about the weather."
      }
    ],
    "reasoning": {
      "effort": "medium"
    }
  }),
})
console.log(await resp.json())

⚠ Responses include reasoning_content artifacts — pass them back unmodified on subsequent turns (dropping them triggers 400s or quality loss).