Z.ai · Balanced

GLM Z1 AirX

Added Apr 15, 2025

Use in the app

Fastest reasoning model in China, with up to 200 tokens per second. The stronger version of GLM Z1 Air.

Tools
Structured output

Input: Text
Output: Text
Discovery tier: Balanced

Pricing

USD per 1M tokens

Input: $0.70
Output: $0.70

Reference prices as published by the model provider. API example

Specifications

Context window: 32K
Max output: 16.4K

Side by side

GLM Z1 AirX compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Limits
	GLM Z1 AirXZ.aiThis model	GLM 5.3 UncensoredZ.aiRemove
Provider	Z.ai	Z.ai
Discovery tier	Balanced	Open weights
Added	Apr 15, 2025	Sep 26, 2026
Context window	32K	1.05MBest
Max output	16.38K	131.07KBest
Average output	—	1.1K tokens
Pricing, USD per 1M tokens
Input	$0.70Best	$1.25
Output	$0.70Best	$2.25
Cache read	—	$0.30
Performance
Throughput	—	38.9 tok/s
Time to first token	—	26.2 s
Request success (24h)	—	98.7%
Capabilities
Reasoning	No	Yes
Tools	Yes	Yes
Structured output	Yes	No
Reasoning effort	—	low, high, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

GLM Z1 AirX
GLM 5.3 Uncensored

Leaderboard	GLM Z1 AirX	GLM 5.3 Uncensored
Usage Share	Not in top 20	#8 · 4.8%

Ranks among Noumen catalog models on Usage leaderboards. Only top-20 placements are listed.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart

curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-z1-airx",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="glm-z1-airx",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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