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Gemma 4 26B A4B Cybersecurity

Added Sep 19, 2026Open weights

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Gemma 4 26B A4B Cybersecurity is a cybersecurity-focused variant based on the uncensored model, with provider moderation for illegal activities. It supports optional reasoning, image understanding, tool calling, and a 262,144-token context window.

  • Reasoning
  • Tools
  • Vision
Input
Text, Images
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.11
Output
$0.33
Cache read
$0.0528

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
32.8K
Average output (7 days)
600 tokens
Longer than 56% of 473 models

Side by side

Gemma 4 26B A4B Cybersecurity compared

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

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Gemma 4 26B A4B CybersecurityGoogleThis modelDiffusionGemmaGoogleRemove
ProviderGoogleGoogle
Discovery tierOpen weightsOpen weights
AddedSep 19, 2026Sep 19, 2026
Limits
Context window262.14K262.14K
Max output32.77K32.77K
Average output600 tokens266 tokens
Pricing, USD per 1M tokens
Input$0.11$0.05Best
Output$0.33$0.15Best
Cache read$0.0528$0.025Best
Performance
Request success (24h)68.0%—
Benchmark indexes
Intelligence Index—9.5
Coding Index—19.7
Capabilities
ReasoningYesYes
ToolsYesNo
VisionYesNo
Reasoning effort—none, xhigh

Public evaluations

Benchmarks

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

  • Gemma 4 26B A4B Cybersecurity
  • DiffusionGemma

Intelligence Index

  • Gemma 4 26B A4B Cybersecurity—
  • DiffusionGemma9.5
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 19.7

Agentic work

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 321 Elo

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 19.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 10.8%

  • GPQA Diamond

    Graduate-level science questions

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 66.9%

  • IFBench

    Following precise output instructions

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 59.5%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemma 4 26B A4B Cybersecurity: —
    • DiffusionGemma: 19.7%

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.

Prompt cache hits
51.5%
About $0.0784 per 1M input tokens with caching
Request success (24h)
68.0%
Failing

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 12.5%
  • 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": "google/gemma-4-26b-a4b-it-cybersecurity",
    "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="google/gemma-4-26b-a4b-it-cybersecurity",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.