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GLM 5.2 Thinking

Added Jun 15, 2026Open weights

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Use in the app

GLM-5.2 with thinking enabled for harder long-horizon coding, autonomous agent workflows, complex engineering optimization, and real-world development tasks.

  • Reasoning
  • Tools
  • Structured output
Input
Text
Output
Text
Reasoning effort
high · max
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.42
Output
$1.32
Cache read
$0.078

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
131.1K
Average output (7 days)
1.8K tokens
Longer than 89% of 468 models

Side by side

GLM 5.2 Thinking 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 ThinkingZ.aiThis modelGLM 5.3 ThinkingZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierOpen weightsOpen weights
AddedJun 15, 2026Aug 14, 2026
Limits
Context window1.05M1.05M
Max output131.07K131.07K
Average output1.8K tokens2.3K tokens
Pricing, USD per 1M tokens
Input$0.42Best$0.60
Output$1.32$1.10Best
Cache read$0.078Best$0.20
Performance
Throughput108.0 tok/s123.3 tok/sBest
Time to first token2.0 sBest7.7 s
Request success (24h)99.7%99.7%
Benchmark indexes
Intelligence Index33.744.8Best
Coding Index68.874.8Best
Capabilities
ReasoningYesYes
ToolsYesYes
Structured outputYesYes
Reasoning efforthigh, maxhigh, max

Public evaluations

Benchmarks

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

  • GLM 5.2 Thinking
  • GLM 5.3 Thinking

Intelligence Index

  • GLM 5.2 Thinking33.7
  • GLM 5.3 Thinking44.8

GLM 5.2 Thinking tested at max reasoning effort

GLM 5.2 Thinking: Better than 76% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 5.2 Thinking: 68.8
    • GLM 5.3 Thinking: 74.8Top

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 5.2 Thinking: 28.4%
    • GLM 5.3 Thinking: 62.2%Top
  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 5.2 Thinking: 6.2%
    • GLM 5.3 Thinking: 29.4%Top
  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • GLM 5.2 Thinking: —
    • GLM 5.3 Thinking: 0.3%
  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 5.2 Thinking: 1,227 Elo
    • GLM 5.3 Thinking: 1,505 EloTop
  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 5.2 Thinking: 1,373 Elo
    • GLM 5.3 Thinking: 1,649 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 5.2 Thinking: 10.4%
    • GLM 5.3 Thinking: 11.2%Top
  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 5.2 Thinking: 78.3%
    • GLM 5.3 Thinking: 79.7%Top
  • MLCR-AA

    Long-context reasoning over medical records

    • GLM 5.2 Thinking: 12.8%
    • GLM 5.3 Thinking: 17.2%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 5.2 Thinking: 41.1%
    • GLM 5.3 Thinking: 42.3%Top
  • GPQA Diamond

    Graduate-level science questions

    • GLM 5.2 Thinking: 89.5%
    • GLM 5.3 Thinking: 91.7%Top
  • IFBench

    Following precise output instructions

    • GLM 5.2 Thinking: 73.3%
    • GLM 5.3 Thinking: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 5.2 Thinking: 1.0%
    • GLM 5.3 Thinking: 41.9%Top
  • SciCode

    Scientific computing in Python

    • GLM 5.2 Thinking: 51.2%
    • GLM 5.3 Thinking: 59.0%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 5.2 Thinking: 50.8%
    • GLM 5.3 Thinking: —
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 5.2 Thinking: 99.1%
    • GLM 5.3 Thinking: —
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 5.2 Thinking: 78.3%
    • GLM 5.3 Thinking: 79.7%Top

Scores from Artificial Analysis, updated Oct 26, 2026. GLM 5.2 Thinking was tested at max reasoning effort; compare scores measured at the same effort.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.

Throughput
108.0 tok/s
Faster than 65% of 254 models
Time to first token
2.0 s
Quicker than 77% of 254 models
Prompt cache hits
59.1%
About $0.22 per 1M input tokens with caching
Request success (24h)
99.7%
Reliable

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.

Hourly request success · last 72 hoursLowest hour 98.2%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

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

Z.ai

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