Model Comparison

Gemini 3 Flash vs Gemma 3n E2B InstructedWhich is better in 2026?

Gemini 3 Flash significantly outperforms across most benchmarks.

Verdict: Gemini 3 Flash vs Gemma 3n E2B Instructed — which is better?

Gemini 3 Flash (by Google) and Gemma 3n E2B Instructed (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.

Gemini 3 Flash outperforms in 2 benchmarks (AIME 2025, GPQA), while Gemma 3n E2B Instructed is better at 0 benchmarks. Gemini 3 Flash significantly outperforms across most benchmarks.

Choose Gemini 3 Flash if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you want the most recent training data — it shipped Dec 2025

Choose Gemma 3n E2B Instructed if…

  • you are already invested in the Google ecosystem
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 3 Flash outperforms in 2 benchmarks (AIME 2025, GPQA), while Gemma 3n E2B Instructed is better at 0 benchmarks.

Gemini 3 Flash significantly outperforms across most benchmarks.

Wed Jun 10 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 3 Flash specifies input context (1,000,000 tokens). Only Gemini 3 Flash specifies output context (65,536 tokens).

Google
Gemini 3 Flash
Input1,000,000 tokens
Output65,536 tokens
Google
Gemma 3n E2B Instructed
Input- tokens
Output- tokens
Wed Jun 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 3 Flash and Gemma 3n E2B Instructed support multimodal inputs.

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

Gemini 3 Flash

Text
Images
Audio
Video

Gemma 3n E2B Instructed

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini 3 Flash

Proprietary

Closed source

Gemma 3n E2B Instructed

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 3 Flash was released on 2025-12-17, while Gemma 3n E2B Instructed was released on 2025-06-26.

Gemini 3 Flash is 6 months newer than Gemma 3n E2B Instructed.

Gemini 3 Flash

Dec 17, 2025

5 months ago

5mo newer
Gemma 3n E2B Instructed

Jun 26, 2025

11 months ago

Knowledge Cutoff

When training data ends

Gemini 3 Flash has a knowledge cutoff of 2025-01-31, while Gemma 3n E2B Instructed has a cutoff of 2024-06-01.

Gemini 3 Flash has more recent training data (up to 2025-01-31), making it potentially better informed about events through that date compared to Gemma 3n E2B Instructed (2024-06-01).

Gemini 3 Flash

Jan 2025

7 mo newer
Gemma 3n E2B Instructed

Jun 2024

Outputs Comparison

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Key Takeaways

Google
Larger context window (1,000,000 tokens)
Higher AIME 2025 score (99.7% vs 6.7%)
Higher GPQA score (90.4% vs 24.8%)
Google

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

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3 Flash
Google
Gemma 3n E2B Instructed

FAQ

Common questions about Gemini 3 Flash vs Gemma 3n E2B Instructed.

Which is better, Gemini 3 Flash or Gemma 3n E2B Instructed?

Gemini 3 Flash significantly outperforms across most benchmarks. Gemini 3 Flash is made by Google and Gemma 3n E2B Instructed is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 3 Flash compare to Gemma 3n E2B Instructed in benchmarks?

Gemini 3 Flash scores Vending-Bench 2: 100.0%, AIME 2025: 99.7%, Global PIQA: 92.8%, MMMLU: 91.8%, GPQA: 90.4%. Gemma 3n E2B Instructed scores HumanEval: 66.5%, MMLU: 60.1%, Global-MMLU-Lite: 59.0%, MBPP: 56.6%, Global-MMLU: 55.1%.

What are the context window sizes for Gemini 3 Flash and Gemma 3n E2B Instructed?

Gemini 3 Flash supports 1.0M tokens and Gemma 3n E2B Instructed supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

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