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Z.ai · Open weights

GLM 4.6 Turbo

Added Oct 2, 2025Open weights

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Use in the app

Fast variant of GLM 4.6 for general chat, coding, and analysis with improved latency and strong reasoning.

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$1.00
Output
$3.00

Reference prices as published by the model provider. API example

Specifications

Context window
204.8K
Max output
131.1K
Average output (7 days)
696 tokens
Longer than 61% of 468 models

Side by side

GLM 4.6 Turbo compared

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

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GLM 4.6 TurboZ.aiThis modelDeepSeek V3.1 Terminus (Thinking)DeepSeekRemove
ProviderZ.aiDeepSeek
Discovery tierOpen weightsOpen weights
AddedOct 2, 2025Jan 1, 2024
Limits
Context window204.8KBest128K
Max output131.07KBest65.54K
Average output696 tokens362 tokens
Pricing, USD per 1M tokens
Input$1.00$0.25Best
Output$3.00$0.70Best
Performance
Throughput—21.6 tok/s
Time to first token—6.4 s
Request success (24h)—99.5%
Benchmark indexes
Intelligence Index14.9Best14.8
Coding Index—43.5
Math Index44.389.7Best
Capabilities
ToolsNoYes
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • GLM 4.6 Turbo
  • DeepSeek V3.1 Terminus (Thinking)

Intelligence Index

  • GLM 4.6 Turbo14.9
  • DeepSeek V3.1 Terminus (Thinking)14.8

GLM 4.6 Turbo: Better than 37% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 43.5

  • Math Index

    Composite of the math evaluations

    • GLM 4.6 Turbo: 44.3
    • DeepSeek V3.1 Terminus (Thinking): 89.7Top

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 2.7%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 0.2%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 458 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 709 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 5.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.6 Turbo: 26.3%
    • DeepSeek V3.1 Terminus (Thinking): 69.3%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.6 Turbo: 5.5%
    • DeepSeek V3.1 Terminus (Thinking): 16.4%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.6 Turbo: 63.2%
    • DeepSeek V3.1 Terminus (Thinking): 79.2%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 4.6 Turbo: 78.4%
    • DeepSeek V3.1 Terminus (Thinking): 85.1%Top

  • IFBench

    Following precise output instructions

    • GLM 4.6 Turbo: 36.7%
    • DeepSeek V3.1 Terminus (Thinking): 57.0%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 0.0%

  • SciCode

    Scientific computing in Python

    • GLM 4.6 Turbo: —
    • DeepSeek V3.1 Terminus (Thinking): 38.0%

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 4.6 Turbo: 56.1%
    • DeepSeek V3.1 Terminus (Thinking): 79.8%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 4.6 Turbo: 44.3%
    • DeepSeek V3.1 Terminus (Thinking): 89.7%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.6 Turbo: 28.8%
    • DeepSeek V3.1 Terminus (Thinking): 30.3%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.6 Turbo: 76.9%Top
    • DeepSeek V3.1 Terminus (Thinking): 37.1%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.6 Turbo: 26.3%
    • DeepSeek V3.1 Terminus (Thinking): 69.3%Top

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

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-4.6-turbo",
    "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-4.6-turbo",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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