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GLM 4.6V Original

Added Dec 8, 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. 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 4.7 Original ThinkingZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierOpen weightsOpen weights
AddedDec 8, 2025Dec 22, 2025
Limits
Context window128K200KBest
Max output24K65.54KBest
Average output258 tokens1.9K tokens
Pricing, USD per 1M tokens
Input$0.60$0.40Best
Output$0.90Best$1.93
Cache read—$0.0801
Performance
Throughput—38.8 tok/s
Time to first token—2.3 s
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index8.422.2Best
Coding Index—45.3
Math Index26.395.0Best
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 4.7 Original Thinking

Intelligence Index

  • GLM 4.6V Original8.4
  • GLM 4.7 Original Thinking22.2

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

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 4.6V Original: —
    • GLM 4.7 Original Thinking: 45.3

  • Math Index

    Composite of the math evaluations

    • GLM 4.6V Original: 26.3
    • GLM 4.7 Original Thinking: 95.0Top

Agentic work

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 4.6V Original: —
    • GLM 4.7 Original Thinking: 1,013 Elo

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.6V Original: 17.0%
    • GLM 4.7 Original Thinking: 71.0%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.6V Original: 3.7%
    • GLM 4.7 Original Thinking: 27.4%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.6V Original: 56.6%
    • GLM 4.7 Original Thinking: 85.9%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 4.6V Original: 75.2%
    • GLM 4.7 Original Thinking: 85.6%Top

  • IFBench

    Following precise output instructions

    • GLM 4.6V Original: 27.9%
    • GLM 4.7 Original Thinking: 67.9%Top

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 4.6V Original: 41.1%
    • GLM 4.7 Original Thinking: 89.4%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 4.6V Original: 26.3%
    • GLM 4.7 Original Thinking: 95.0%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.6V Original: 3.0%
    • GLM 4.7 Original Thinking: 31.8%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.6V Original: 30.7%
    • GLM 4.7 Original Thinking: 95.9%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.6V Original: 17.0%
    • GLM 4.7 Original Thinking: 71.0%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)

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