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Z.ai · Open weights

GLM 5.3 Flash Cybersecurity

Added Sep 19, 2026Open weights

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GLM 5.3 Flash Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports always-on reasoning, image understanding, tool calling, and a 1,048,576-token context window.

  • Reasoning
  • Tools
  • Vision
Input
Text, Images
Output
Text
Reasoning effort
low · high · max
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.15
Output
$0.50
Cache read
$0.075

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
32.8K
Average output (7 days)
417 tokens
Longer than 42% of 468 models

Side by side

GLM 5.3 Flash Cybersecurity compared

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

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GLM 5.3 Flash CybersecurityZ.aiThis modelGemma 4 31B IT TEEGoogleRemove
ProviderZ.aiGoogle
Discovery tierOpen weightsOpen weights
AddedSep 19, 2026May 26, 2026
Limits
Context window1.05MBest262.14K
Max output32.77K262.14KBest
Average output417 tokens269 tokens
Pricing, USD per 1M tokens
Input$0.15$0.15
Output$0.50$0.46Best
Cache read$0.075—
Performance
Throughput13.3 tok/s62.7 tok/sBest
Time to first token6.7 s3.9 sBest
Request success (24h)96.1%99.8%Best
Benchmark indexes
Intelligence Index—14.7
Coding Index—43.4
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesNo
Reasoning effortlow, high, max—

Public evaluations

Benchmarks

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

  • GLM 5.3 Flash Cybersecurity
  • Gemma 4 31B IT TEE

Intelligence Index

  • GLM 5.3 Flash Cybersecurity—
  • Gemma 4 31B IT TEE14.7
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 43.4

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 4.9%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 0.5%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 368 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 619 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 6.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 69.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 23.6%

  • GPQA Diamond

    Graduate-level science questions

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 85.7%

  • IFBench

    Following precise output instructions

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 75.6%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 0.0%

  • SciCode

    Scientific computing in Python

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 45.5%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 36.4%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 59.9%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 5.3 Flash Cybersecurity: —
    • Gemma 4 31B IT TEE: 69.7%

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
13.3 tok/s
Faster than 4% of 254 models
Time to first token
6.7 s
Quicker than 23% of 254 models
Prompt cache hits
93.5%
About $0.0798 per 1M input tokens with caching
Request success (24h)
96.1%
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 50.9%
  • 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-5.3-flash-cybersecurity",
    "reasoning_effort": "low",
    "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-5.3-flash-cybersecurity",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

Other Z.ai models, starting with the same family.