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DiffusionGemma

Added Sep 19, 2026Open weights

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DiffusionGemma is a high-speed diffusion-based version of Gemma 4 26B A4B. It supports optional reasoning and a 262,144-token context window. Temperature, min-p, seed, minimum output tokens, logit bias, bad words, and allowed token IDs are unavailable; omit these parameters to use native diffusion sampling.

  • Reasoning
Input
Text
Output
Text
Reasoning effort
none · xhigh
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.05
Output
$0.15
Cache read
$0.025

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
32.8K
Average output (7 days)
266 tokens
Longer than 28% of 473 models

Side by side

DiffusionGemma compared

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

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DiffusionGemmaGoogleThis modelGemma 4 26B A4B CybersecurityGoogleRemove
ProviderGoogleGoogle
Discovery tierOpen weightsOpen weights
AddedSep 19, 2026Sep 19, 2026
Limits
Context window262.14K262.14K
Max output32.77K32.77K
Average output266 tokens600 tokens
Pricing, USD per 1M tokens
Input$0.05Best$0.11
Output$0.15Best$0.33
Cache read$0.025Best$0.0528
Performance
Request success (24h)—68.0%
Benchmark indexes
Intelligence Index9.5—
Coding Index19.7—
Capabilities
ReasoningYesYes
ToolsNoYes
VisionNoYes
Reasoning effortnone, xhigh—

Public evaluations

Benchmarks

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

  • DiffusionGemma
  • Gemma 4 26B A4B Cybersecurity

Intelligence Index

  • DiffusionGemma9.5
  • Gemma 4 26B A4B Cybersecurity—

DiffusionGemma: Better than 19% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

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

Agentic work

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

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

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

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

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

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

  • GPQA Diamond

    Graduate-level science questions

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

  • IFBench

    Following precise output instructions

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

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

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

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
0.0%
About $0.05 per 1M input tokens with caching

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.

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/diffusiongemma",
    "reasoning_effort": "none",
    "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/diffusiongemma",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.