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GLM 4.6V Original

Added Dec 8, 2025Open weights

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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. Direct via Z-AI (Zhipu).

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

Pricing

USD per 1M tokens
Input
$0.60
Output
$0.90

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
24K
Average output (7 days)
258 tokens
Longer than 27% of 468 models

Side by side

GLM 4.6V Original compared

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

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GLM 4.6V OriginalZ.aiThis modelGLM 5 OriginalZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierOpen weightsOpen weights
AddedDec 8, 2025Feb 11, 2026
Limits
Context window128K200KBest
Max output24K128KBest
Average output258 tokens250 tokens
Pricing, USD per 1M tokens
Input$0.60$0.60
Output$0.90Best$1.90
Cache read—$0.10
Performance
Request success (24h)—99.7%
Benchmark indexes
Intelligence Index8.427.9Best
Math Index26.3—
Capabilities
ReasoningNoYes
ToolsNoYes
VisionYesNo
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • GLM 4.6V Original
  • GLM 5 Original

Intelligence Index

  • GLM 4.6V Original8.4
  • GLM 5 Original27.9

GLM 4.6V Original: Better than 13% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • GLM 4.6V Original: 26.3
    • GLM 5 Original: —

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.6V Original: 17.0%
    • GLM 5 Original: 75.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.6V Original: 3.7%
    • GLM 5 Original: 29.3%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.6V Original: 56.6%
    • GLM 5 Original: 82.0%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 4.6V Original: 75.2%
    • GLM 5 Original: —

  • IFBench

    Following precise output instructions

    • GLM 4.6V Original: 27.9%
    • GLM 5 Original: 72.3%Top

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 4.6V Original: 41.1%
    • GLM 5 Original: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 4.6V Original: 26.3%
    • GLM 5 Original: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.6V Original: 3.0%
    • GLM 5 Original: 43.2%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.6V Original: 30.7%
    • GLM 5 Original: 98.2%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.6V Original: 17.0%
    • GLM 5 Original: 75.7%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-4.6v-original",
    "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-original",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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