Model Comparison

Gemma 3 12B vs Gemma 3 4B

Gemma 3 12B significantly outperforms across most benchmarks. Gemma 3 4B is 2.5x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

26 benchmarks

Gemma 3 12B outperforms in 25 benchmarks (AI2D, BIG-Bench Extra Hard, BIG-Bench Hard, Bird-SQL (dev), ChartQA, DocVQA, ECLeKTic, FACTS Grounding, Global-MMLU-Lite, GPQA, GSM8k, HiddenMath, HumanEval, InfoVQA, LiveCodeBench, MATH, MathVista-Mini, MBPP, MMLU-Pro, MMMU (val), Natural2Code, SimpleQA, TextVQA, VQAv2 (val), WMT24++), while Gemma 3 4B is better at 1 benchmark (IFEval).

Gemma 3 12B significantly outperforms across most benchmarks.

Thu Apr 09 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 4B costs less

For input processing, Gemma 3 12B ($0.05/1M tokens) is 2.5x more expensive than Gemma 3 4B ($0.02/1M tokens).

For output processing, Gemma 3 12B ($0.10/1M tokens) is 2.5x more expensive than Gemma 3 4B ($0.04/1M tokens).

In conclusion, Gemma 3 12B is more expensive than Gemma 3 4B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Apr 09 2026 • llm-stats.com
Google
Gemma 3 12B
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
Google
Gemma 3 4B
Input tokens$0.02
Output tokens$0.04
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

8.0B diff

Gemma 3 12B has 8.0B more parameters than Gemma 3 4B, making it 200.0% larger.

Google
Gemma 3 12B
12.0Bparameters
Google
Gemma 3 4B
4.0Bparameters
12.0B
Gemma 3 12B
4.0B
Gemma 3 4B

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.

Google
Gemma 3 12B
Input131,072 tokens
Output131,072 tokens
Google
Gemma 3 4B
Input131,072 tokens
Output131,072 tokens
Thu Apr 09 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 12B and Gemma 3 4B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 3 12B

Text
Images
Audio
Video

Gemma 3 4B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Gemma.

Both models share the same licensing terms, providing consistent usage rights.

Gemma 3 12B

Gemma

Open weights

Gemma 3 4B

Gemma

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-03-12.

They likely represent similar generations of model development.

Gemma 3 12B

Mar 12, 2025

1.1 years ago

Gemma 3 4B

Mar 12, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while Gemma 3 12B's cutoff date is not specified.

We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without Gemma 3 12B's cutoff date.

Gemma 3 12B

—

Gemma 3 4B

Aug 2024

Provider Availability

Gemma 3 12B is available from DeepInfra. Gemma 3 4B is available from DeepInfra.

Gemma 3 12B

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M

Gemma 3 4B

deepinfra logo
Deepinfra
Input Price:Input: $0.02/1MOutput Price:Output: $0.04/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Google
Higher AI2D score (84.2% vs 74.8%)
Higher BIG-Bench Extra Hard score (16.3% vs 11.0%)
Higher BIG-Bench Hard score (85.7% vs 72.2%)
Higher Bird-SQL (dev) score (47.9% vs 36.3%)
Higher ChartQA score (75.7% vs 68.8%)
Higher DocVQA score (87.1% vs 75.8%)
Higher ECLeKTic score (10.3% vs 4.6%)
Higher FACTS Grounding score (75.8% vs 70.1%)
Higher Global-MMLU-Lite score (69.5% vs 54.5%)
Higher GPQA score (40.9% vs 30.8%)
Higher GSM8k score (94.4% vs 89.2%)
Higher HiddenMath score (54.5% vs 43.0%)
Higher HumanEval score (85.4% vs 71.3%)
Higher InfoVQA score (64.9% vs 50.0%)
Higher LiveCodeBench score (24.6% vs 12.6%)
Higher MATH score (83.8% vs 75.6%)
Higher MathVista-Mini score (62.9% vs 50.0%)
Higher MBPP score (73.0% vs 63.2%)
Higher MMLU-Pro score (60.6% vs 43.6%)
Higher MMMU (val) score (59.6% vs 48.8%)
Higher Natural2Code score (80.7% vs 70.3%)
Higher SimpleQA score (6.3% vs 4.0%)
Higher TextVQA score (67.7% vs 57.8%)
Higher VQAv2 (val) score (71.6% vs 62.4%)
Higher WMT24++ score (51.6% vs 46.8%)
Google
Less expensive input tokens
Less expensive output tokens
Higher IFEval score (90.2% vs 88.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3 12B
Google
Gemma 3 4B

FAQ

Common questions about Gemma 3 12B vs Gemma 3 4B

Gemma 3 12B significantly outperforms across most benchmarks. Gemma 3 12B is made by Google and Gemma 3 4B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 3 12B scores GSM8k: 94.4%, IFEval: 88.9%, DocVQA: 87.1%, BIG-Bench Hard: 85.7%, HumanEval: 85.4%. Gemma 3 4B scores IFEval: 90.2%, GSM8k: 89.2%, DocVQA: 75.8%, MATH: 75.6%, AI2D: 74.8%.
Gemma 3 4B is 2.5x cheaper for input tokens. Gemma 3 12B costs $0.05/M input and $0.10/M output via deepinfra. Gemma 3 4B costs $0.02/M input and $0.04/M output via deepinfra.
Gemma 3 12B supports 131K tokens and Gemma 3 4B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.05 vs $0.02/M). See the full comparison above for benchmark-by-benchmark results.