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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 468 models

Side by side

GLM 5.2 TEE compared

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

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GLM 5.2 TEEZ.aiThis modelKimi K2 ThinkingMoonshotRemove
ProviderZ.aiMoonshot
Discovery tierOpen weightsOpen weights
AddedJun 16, 2026Nov 6, 2025
Limits
Context window1.05MBest262.14K
Max output131.07KBest98.3K
Average output1.5K tokens1.9K tokens
Pricing, USD per 1M tokens
Input$1.40$0.60Best
Output$4.40$2.50Best
Cache read$0.70$0.15Best
Performance
Throughput—78.6 tok/s
Time to first token—4.6 s
Request success (24h)66.6%99.6%Best
Benchmark indexes
Intelligence Index22.4Best22.0
Coding Index46.5—
Math Index—94.7
Capabilities
ReasoningYesYes
ToolsYesYes
Structured outputYesYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • GLM 5.2 TEE
  • Kimi K2 Thinking

Intelligence Index

  • GLM 5.2 TEE22.4
  • Kimi K2 Thinking22.0

GLM 5.2 TEE: Better than 54% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 5.2 TEE: 46.5
    • Kimi K2 Thinking: —

  • Math Index

    Composite of the math evaluations

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 94.7

Agentic work

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 5.2 TEE: 1,244 Elo
    • Kimi K2 Thinking: —

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 5.2 TEE: 42.3%
    • Kimi K2 Thinking: 72.0%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 5.2 TEE: 9.8%
    • Kimi K2 Thinking: 23.8%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 5.2 TEE: 68.6%
    • Kimi K2 Thinking: 83.8%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 84.8%

  • IFBench

    Following precise output instructions

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 68.1%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 85.3%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 94.7%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 31.1%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 5.2 TEE: —
    • Kimi K2 Thinking: 93.0%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 5.2 TEE: 42.3%
    • Kimi K2 Thinking: 72.0%Top

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
0.4%
About $1.40 per 1M input tokens with caching
Request success (24h)
66.6%

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)

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