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Z.ai · Open weights

GLM 4.6V

Added Dec 11, 2025Open weights

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Use in the app

GLM-4.6V scales its context window to 128k tokens in training, and achieves SoTA performance in visual understanding among models of similar parameter scales. Integrates native Function Calling capabilities, bridging 'visual perception' and 'executable action' for multimodal agents. Quantized at FP8.

  • Vision
  • Video input
Input
Text, Images, Video
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.30
Output
$0.90

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
24K
Average output (7 days)
139 tokens
Longer than 14% of 465 models

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Public evaluations

Benchmarks

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

Intelligence Index

8.4

Better than 13% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    26.3

    Composite of the math evaluations

    Better than 25% of 118 scored models

Document reasoning

  • AA-LCRv1.1

    17.0%

    Reasoning across long documents

    Better than 6% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    3.7%

    Expert-level questions across academic fields

    Better than 4% of 323 scored models

  • GPQA Diamond

    56.6%

    Graduate-level science questions

    Better than 14% of 291 scored models

  • MMLU-Pro

    75.2%

    Multi-subject knowledge and reasoning

    Better than 34% of 132 scored models

  • IFBench

    27.9%

    Following precise output instructions

    Better than 2% of 215 scored models

Coding

  • LiveCodeBench

    41.1%

    Recent competitive programming problems

    Better than 35% of 129 scored models

Math

  • AIME 2025

    26.3%

    Competition mathematics, 2025 problems

    Better than 25% of 118 scored models

Legacy evaluations

  • Terminal-Bench Hard

    3.0%

    Earlier terminal task suite

    Better than 6% of 212 scored models

  • τ²-Bench Telecom

    30.7%

    Tool use in a customer-support simulation

    Better than 21% of 214 scored models

  • AA-LCR (unversioned)

    17.0%

    Long-context reasoning, earlier grading

    Better than 6% 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
28.4%
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 96.4%
  • 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-4.6v",
    "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-4.6v",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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