GLM-5.3-Flash

glm-5.3-flash 🇨🇭 Switzerland

Z.ai's model for code, reasoning and agents (on trial from 4 November 2026). 320 billion parameters, about 18 billion at work on each token. In our trials on PHP and Python it wrote correct code more often than any other model here, and it calls your functions. It always thinks before answering, without showing it, and the thinking counts in your tokens: as much as it needs by default, briefly with reasoning_effort "low". Context of 262,144 tokens, 4-bit NVFP4 weights by NVIDIA. Runs on NVIDIA, in Switzerland. On trial.

At a glance

Publisher	Z.ai
Architecture	Mixture of experts, 320 billion parameters, about 18 billion per token
Licence	MIT
Precision	NVFP4, 4 bits (NVIDIA)
Context	262,144 tokens, prompt and answer together
Longest answer	`max_tokens` up to 32,768, reasoning included
Reads	Text
Calls tools	Yes
JSON schema	Yes
Reasons	Yes, always, at three levels: reasoning_effort "low", "medium" or "high". The reasoning counts as output tokens.
Runs in	🇨🇭 Switzerland
Status	Loaded: the first request answers without a start-up wait. Live state on Status.

Use it

curl https://api.ai.itsincom.org/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3-flash",
    "messages": [{"role": "user", "content": "Summarise in one line: the meeting moves to Thursday at 10."}]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.ai.itsincom.org/v1", api_key=os.environ["API_KEY"])
answer = client.chat.completions.create(
    model="glm-5.3-flash",
    messages=[{"role": "user", "content": "Summarise in one line: the meeting moves to Thursday at 10."}],
)
print(answer.choices[0].message.content)

More in Quickstart and Chat completions.

Limits

Prompt and answer together stay within 262,144 tokens; beyond that the engine refuses the request with a 400 that says so.
The reasoning counts against max_tokens: a low cap can end the answer before it starts, with finish_reason: "length".
Text only: a request with an image gets a 400.
Served at 4 bits, which makes it faster and fits our machines; we write the precision of every model.
A request goes only to the zones your key allows; if the model has no machine there now, a 503 names the zones. It is never sent elsewhere.