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GLM 5.2 TEE

Added Jun 16, 2026Open weights

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Use in the app

GLM-5.2 is Z.AI's flagship model for long-horizon tasks and autonomous workflows, with a 1M-token context window. Running inside a TEE (Trusted Execution Environment), with attestation support.

  • Reasoning
  • Tools
  • Structured output
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$1.40
Output
$4.40
Cache read
$0.70

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
131.1K
Average output (7 days)
1.5K tokens
Longer than 85% of 465 models

Side by side

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TryGemini 3.5 Flash LiteKimi K2 ThinkingMiniMax M2.7All 3

Public evaluations

Benchmarks

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

Intelligence Index

22.4

Better than 54% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    46.5

    Composite of the coding evaluations

    Better than 42% of 168 scored models

Agentic work

  • GDPval-AAv2.1

    1,244 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 55% of 187 scored models

Document reasoning

  • AA-LCRv1.1

    42.3%

    Reasoning across long documents

    Better than 19% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    9.8%

    Expert-level questions across academic fields

    Better than 31% of 323 scored models

  • GPQA Diamond

    68.6%

    Graduate-level science questions

    Better than 28% of 291 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    42.3%

    Long-context reasoning, earlier grading

    Better than 19% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
99.5%
About $0.70 per 1M input tokens with caching

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

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": "TEE/glm-5.2",
    "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="TEE/glm-5.2",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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