NOUMENOpen app
NOUMEN

Google · Open weights

Gemma 3 4B IT

Added Jan 1, 2024Open weights

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Use in the app

Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions.

  • PDF input
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.20
Output
$0.20

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
8.2K
Average output (7 days)
115 tokens
Longer than 11% of 468 models

Side by side

Gemma 3 4B IT compared

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

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Gemma 3 4B ITGoogleThis modelMinistral 3BMistralRemove
ProviderGoogleMistral
Discovery tierOpen weightsOpen weights
AddedJan 1, 2024Dec 4, 2025
Limits
Context window128K131.07KBest
Max output8.19K32.77KBest
Average output115 tokens54 tokens
Pricing, USD per 1M tokens
Input$0.20$0.10Best
Output$0.20$0.10Best
Performance
Request success (24h)100.0%—
Benchmark indexes
Intelligence Index4.84.8
Coding Index2.74.8Best
Math Index12.722.0Best
Capabilities
PDF inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • Gemma 3 4B IT
  • Ministral 3B

Intelligence Index

  • Gemma 3 4B IT4.8
  • Ministral 3B4.8

Gemma 3 4B IT: Better than 0% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemma 3 4B IT: 2.7
    • Ministral 3B: 4.8Top

  • Math Index

    Composite of the math evaluations

    • Gemma 3 4B IT: 12.7
    • Ministral 3B: 22.0Top

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Gemma 3 4B IT: —
    • Ministral 3B: 0.7%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Gemma 3 4B IT: —
    • Ministral 3B: 0.0%

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemma 3 4B IT: —
    • Ministral 3B: 29 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Gemma 3 4B IT: —
    • Ministral 3B: 0.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemma 3 4B IT: 6.7%
    • Ministral 3B: 17.0%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Gemma 3 4B IT: —
    • Ministral 3B: 0.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemma 3 4B IT: 5.3%
    • Ministral 3B: 5.4%Top

  • GPQA Diamond

    Graduate-level science questions

    • Gemma 3 4B IT: 29.1%
    • Ministral 3B: 35.8%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Gemma 3 4B IT: 41.7%
    • Ministral 3B: 52.4%Top

  • IFBench

    Following precise output instructions

    • Gemma 3 4B IT: 28.3%Top
    • Ministral 3B: 26.8%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Gemma 3 4B IT: —
    • Ministral 3B: 0.0%

  • SciCode

    Scientific computing in Python

    • Gemma 3 4B IT: —
    • Ministral 3B: 15.3%

  • LiveCodeBench

    Recent competitive programming problems

    • Gemma 3 4B IT: 11.2%
    • Ministral 3B: 24.7%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Gemma 3 4B IT: 12.7%
    • Ministral 3B: 22.0%Top

  • AIME

    Competition mathematics

    • Gemma 3 4B IT: 6.3%
    • Ministral 3B: —

  • MATH-500

    Competition math problems

    • Gemma 3 4B IT: 76.6%
    • Ministral 3B: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Gemma 3 4B IT: 0.8%Top
    • Ministral 3B: 0.0%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Gemma 3 4B IT: 5.0%
    • Ministral 3B: 24.9%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemma 3 4B IT: 6.7%
    • Ministral 3B: 17.0%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.

Request success (24h)
100.0%
Reliable
Hourly request success · last 72 hoursLowest hour 66.6%
  • 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": "unsloth/gemma-3-4b-it",
    "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="unsloth/gemma-3-4b-it",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.