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GLM 4.5

Added Apr 15, 2025Open weights

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Use in the app

GLM-4.5 is a Mixture-of-Experts model built for agent-based applications, with 355B total / 32B active parameters and up to 128k context. It supports reasoning, code generation, and agent workflows.

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.30
Output
$1.30

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
65.5K
Average output (7 days)
696 tokens
Longer than 62% of 468 models

Side by side

GLM 4.5 compared

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

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GLM 4.5Z.aiThis modelKimi K2 0711 FastMoonshotRemove
ProviderZ.aiMoonshot
Discovery tierOpen weightsOpen weights
AddedApr 15, 2025Dec 15, 2025
Limits
Context window128K131.07KBest
Max output65.54KBest16.38K
Average output696 tokens—
Pricing, USD per 1M tokens
Input$0.30Best$0.40
Output$1.30Best$1.80
Performance
Throughput35.7 tok/s—
Time to first token9.6 s—
Request success (24h)100.0%—
Benchmark indexes
Intelligence Index12.8Best12.7
Math Index73.7Best57.0
Capabilities
PDF inputNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • GLM 4.5
  • Kimi K2 0711 Fast

Intelligence Index

  • GLM 4.512.8
  • Kimi K2 0711 Fast12.7

GLM 4.5: Better than 29% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • GLM 4.5: 73.7Top
    • Kimi K2 0711 Fast: 57.0

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.5: 52.7%
    • Kimi K2 0711 Fast: 53.0%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.5: 13.0%Top
    • Kimi K2 0711 Fast: 7.4%

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.5: 78.2%Top
    • Kimi K2 0711 Fast: 76.6%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 4.5: 83.5%Top
    • Kimi K2 0711 Fast: 82.4%

  • IFBench

    Following precise output instructions

    • GLM 4.5: 44.1%Top
    • Kimi K2 0711 Fast: 41.5%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 4.5: 73.8%Top
    • Kimi K2 0711 Fast: 55.6%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 4.5: 73.7%Top
    • Kimi K2 0711 Fast: 57.0%

  • AIME

    Competition mathematics

    • GLM 4.5: 87.3%Top
    • Kimi K2 0711 Fast: 69.3%

  • MATH-500

    Competition math problems

    • GLM 4.5: 97.9%Top
    • Kimi K2 0711 Fast: 97.1%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.5: 22.0%Top
    • Kimi K2 0711 Fast: 15.9%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.5: 43.0%
    • Kimi K2 0711 Fast: 61.1%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.5: 52.7%
    • Kimi K2 0711 Fast: 53.0%Top

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
35.7 tok/s
Faster than 25% of 254 models
Time to first token
9.6 s
Quicker than 11% of 254 models
Prompt cache hits
26.4%
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-4.5",
    "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-4.5",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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