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Z.ai · Open weights

GLM 4.5

Added Apr 15, 2025Open weights

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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 modelNvidia Nemotron 3 Super 120BnvidiaRemove
ProviderZ.ainvidia
Discovery tierOpen weightsOpen weights
AddedApr 15, 2025Mar 1, 2026
Limits
Context window128K262.14KBest
Max output65.54KBest16.38K
Average output696 tokens431 tokens
Pricing, USD per 1M tokens
Input$0.30$0.05Best
Output$1.30$0.25Best
Performance
Throughput35.7 tok/s—
Time to first token9.6 s—
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index12.812.8
Coding Index—37.7
Math Index73.7—
Capabilities
ReasoningNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • GLM 4.5
  • Nvidia Nemotron 3 Super 120B

Intelligence Index

  • GLM 4.512.8
  • Nvidia Nemotron 3 Super 120B12.8

GLM 4.5: Better than 29% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 37.7

  • Math Index

    Composite of the math evaluations

    • GLM 4.5: 73.7
    • Nvidia Nemotron 3 Super 120B: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 3.8%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 0.3%

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 490 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 2.6%

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.5: 52.7%
    • Nvidia Nemotron 3 Super 120B: 65.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.5: 13.0%
    • Nvidia Nemotron 3 Super 120B: 20.8%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.5: 78.2%
    • Nvidia Nemotron 3 Super 120B: 80.0%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 4.5: 83.5%
    • Nvidia Nemotron 3 Super 120B: —

  • IFBench

    Following precise output instructions

    • GLM 4.5: 44.1%
    • Nvidia Nemotron 3 Super 120B: 71.5%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 0.0%

  • SciCode

    Scientific computing in Python

    • GLM 4.5: —
    • Nvidia Nemotron 3 Super 120B: 36.2%

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 4.5: 73.8%
    • Nvidia Nemotron 3 Super 120B: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 4.5: 73.7%
    • Nvidia Nemotron 3 Super 120B: —

  • AIME

    Competition mathematics

    • GLM 4.5: 87.3%
    • Nvidia Nemotron 3 Super 120B: —

  • MATH-500

    Competition math problems

    • GLM 4.5: 97.9%
    • Nvidia Nemotron 3 Super 120B: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.5: 22.0%
    • Nvidia Nemotron 3 Super 120B: 28.8%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.5: 43.0%
    • Nvidia Nemotron 3 Super 120B: 67.8%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.5: 52.7%
    • Nvidia Nemotron 3 Super 120B: 65.7%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
45.5%
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)

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