NOUMENOpen app

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 modelCohere: Command R+cohereRemove
ProviderGooglecohere
Discovery tierOpen weightsBalanced
AddedJan 1, 2024Jan 1, 2024
Limits
Context window128K128K
Max output8.19KBest4.1K
Average output115 tokens146 tokens
Pricing, USD per 1M tokens
Input$0.20Best$2.86
Output$0.20Best$14.25
Performance
Request success (24h)100.0%—
Benchmark indexes
Intelligence Index4.85.3Best
Coding Index2.7—
Math Index12.7—
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
  • Cohere: Command R+

Intelligence Index

  • Gemma 3 4B IT4.8
  • Cohere: Command R+5.3

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
    • Cohere: Command R+: —
  • Math Index

    Composite of the math evaluations

    • Gemma 3 4B IT: 12.7
    • Cohere: Command R+: —

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemma 3 4B IT: 6.7%
    • Cohere: Command R+: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemma 3 4B IT: 5.3%Top
    • Cohere: Command R+: 4.6%
  • GPQA Diamond

    Graduate-level science questions

    • Gemma 3 4B IT: 29.1%
    • Cohere: Command R+: 32.3%Top
  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Gemma 3 4B IT: 41.7%
    • Cohere: Command R+: 43.2%Top
  • IFBench

    Following precise output instructions

    • Gemma 3 4B IT: 28.3%
    • Cohere: Command R+: —

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Gemma 3 4B IT: 11.2%
    • Cohere: Command R+: 12.2%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Gemma 3 4B IT: 12.7%
    • Cohere: Command R+: —
  • AIME

    Competition mathematics

    • Gemma 3 4B IT: 6.3%Top
    • Cohere: Command R+: 0.7%
  • MATH-500

    Competition math problems

    • Gemma 3 4B IT: 76.6%Top
    • Cohere: Command R+: 27.9%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Gemma 3 4B IT: 0.8%
    • Cohere: Command R+: —
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Gemma 3 4B IT: 5.0%
    • Cohere: Command R+: —
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemma 3 4B IT: 6.7%
    • Cohere: Command R+: —

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)
99.8%
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.