Model Comparison

Gemma 4 12B vs Gemma 4 E2BWhich is better in 2026?

Gemma 4 12B significantly outperforms across most benchmarks.

Verdict: Gemma 4 12B vs Gemma 4 E2B — which is better?

Gemma 4 12B (by Google) and Gemma 4 E2B (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Gemma 4 12B outperforms in 10 benchmarks (AIME 2026, BIG-Bench Extra Hard, GPQA, LiveCodeBench v6, MathVision, MedXpertQA, MMLU-Pro, MMMLU, MMMU-Pro, MRCR v2 (8-needle)), while Gemma 4 E2B is better at 0 benchmarks. Gemma 4 12B significantly outperforms across most benchmarks.

Choose Gemma 4 12B if…

  • you want the strongest raw capability — it leads on 10 of 10 shared benchmarks
  • you want the most recent training data — it shipped May 2026

Choose Gemma 4 E2B if…

  • you are already invested in the Google ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

10 benchmarks

Gemma 4 12B outperforms in 10 benchmarks (AIME 2026, BIG-Bench Extra Hard, GPQA, LiveCodeBench v6, MathVision, MedXpertQA, MMLU-Pro, MMMLU, MMMU-Pro, MRCR v2 (8-needle)), while Gemma 4 E2B is better at 0 benchmarks.

Gemma 4 12B significantly outperforms across most benchmarks.

Fri Jul 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

6.9B diff

Gemma 4 12B has 6.9B more parameters than Gemma 4 E2B, making it 134.5% larger.

Google
Gemma 4 12B
12.0Bparameters
Google
Gemma 4 E2B
5.1Bparameters
12.0B
Gemma 4 12B
5.1B
Gemma 4 E2B

Input Capabilities

Supported data types and modalities

Both Gemma 4 12B and Gemma 4 E2B support multimodal inputs.

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

Gemma 4 12B

Text
Images
Audio
Video

Gemma 4 E2B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

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

Gemma 4 12B

Apache 2.0

Open weights

Gemma 4 E2B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 4 12B was released on 2026-05-23, while Gemma 4 E2B was released on 2026-04-02.

Gemma 4 12B is 2 months newer than Gemma 4 E2B.

Gemma 4 12B

May 23, 2026

1 months ago

1mo newer
Gemma 4 E2B

Apr 2, 2026

3 months ago

Knowledge Cutoff

When training data ends

Both models have the same knowledge cutoff date of 2025-01-01.

They should have similar awareness of historical events and information up to this date.

Gemma 4 12B

Jan 2025

Gemma 4 E2B

Jan 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Higher AIME 2026 score (77.5% vs 37.5%)
Higher BIG-Bench Extra Hard score (53.0% vs 21.9%)
Higher GPQA score (78.8% vs 43.4%)
Higher LiveCodeBench v6 score (72.0% vs 44.0%)
Higher MathVision score (79.7% vs 52.4%)
Higher MedXpertQA score (48.7% vs 23.5%)
Higher MMLU-Pro score (77.2% vs 60.0%)
Higher MMMLU score (83.4% vs 67.4%)
Higher MMMU-Pro score (69.1% vs 44.2%)
Higher MRCR v2 (8-needle) score (43.4% vs 19.1%)
Google

No standout differentiators in the data we have for this pair.

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemma 4 12B and Gemma 4 E2B side-by-side, then vote on the output you prefer.

Gemma 4 12B
✓ Preferred
Gemma 4 E2B
Open in Playground
AI Model Comparison Table
Feature
Google
Gemma 4 12B
Google
Gemma 4 E2B

FAQ

Common questions about Gemma 4 12B vs Gemma 4 E2B.

Which is better, Gemma 4 12B or Gemma 4 E2B?

Gemma 4 12B significantly outperforms across most benchmarks. Gemma 4 12B is made by Google and Gemma 4 E2B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 4 12B compare to Gemma 4 E2B in benchmarks?

Gemma 4 12B scores FLEURS: 93.1%, MMMLU: 83.4%, MathVision: 79.7%, GPQA: 78.8%, AIME 2026: 77.5%. Gemma 4 E2B scores MMMLU: 67.4%, MMLU-Pro: 60.0%, MathVision: 52.4%, MMMU-Pro: 44.2%, LiveCodeBench v6: 44.0%.

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