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Z.ai · Open weights

GLM 5V Turbo

Added Apr 1, 2026Open weights

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Use in the app

Z.ai's native multimodal agent model for vision-based coding and agent workflows. This is the standard non-thinking variant for image, video, and text inputs, tuned for perceive-plan-execute loops, complex coding, and tool-driven task execution.

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

Pricing

USD per 1M tokens
Input
$1.20
Output
$4.00
Cache read
$0.24

Reference prices as published by the model provider. API example

Specifications

Context window
202.8K
Max output
131.1K
Average output (7 days)
214 tokens
Longer than 22% of 468 models

Side by side

GLM 5V Turbo compared

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

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GLM 5V TurboZ.aiThis modelGLM 5V Turbo ThinkingZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierOpen weightsOpen weights
AddedApr 1, 2026Apr 2, 2026
Limits
Context window202.8K202.8K
Max output131.07K131.07K
Average output214 tokens942 tokens
Pricing, USD per 1M tokens
Input$1.20$1.20
Output$4.00$4.00
Cache read$0.24$0.24
Performance
Throughput122.6 tok/sBest41.0 tok/s
Time to first token6.3 sBest6.5 s
Request success (24h)100.0%Best97.6%
Benchmark indexes
Intelligence Index—23.5
Capabilities
ReasoningNoYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
Video inputYesYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • GLM 5V Turbo
  • GLM 5V Turbo Thinking

Intelligence Index

  • GLM 5V Turbo—
  • GLM 5V Turbo Thinking23.5
3.8Catalog models by score55.1

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 70.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 17.1%
  • GPQA Diamond

    Graduate-level science questions

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 80.9%
  • IFBench

    Following precise output instructions

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 61.1%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 32.6%
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 98.5%
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 5V Turbo: —
    • GLM 5V Turbo Thinking: 70.3%

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.

Throughput
122.6 tok/s
Faster than 70% of 254 models
Time to first token
6.3 s
Quicker than 28% of 254 models
Prompt cache hits
88.0%
About $0.35 per 1M input tokens with caching
Request success (24h)
100.0%
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 100.0%
  • 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-5v-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-5v-turbo",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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