Google · Open weights
Gemma 3 4B IT
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.
| Gemma 3 4B ITGoogleThis model | Cohere: Command R+cohereRemove | |
|---|---|---|
| Provider | cohere | |
| Discovery tier | Open weights | Balanced |
| Added | Jan 1, 2024 | Jan 1, 2024 |
| Limits | ||
| Context window | 128K | 128K |
| Max output | 8.19KBest | 4.1K |
| Average output | 115 tokens | 146 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 Index | 4.8 | 5.3Best |
| Coding Index | 2.7 | — |
| Math Index | 12.7 | — |
| Capabilities | ||
| PDF input | Yes | No |
| 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
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
- 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.
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)Related models
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