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Gemini 2.0 Flash Thinking vs Gemma 3 4B

Gemini 2.0 Flash Thinking leads the LLM Stats Score 16.7 to -1.9.

Google · Google · Updated for 2026

Which is better?

Gemini 2.0 Flash Thinking leads the overall LLM Stats Score 16.7 to -1.9, ranking #220 overall.

In the 1 individual benchmarks reported for both models, Gemini 2.0 Flash Thinking wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 2.0 Flash Thinking

  • overall performance matters — it scores 16.7 and ranks #220 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

Choose Gemma 3 4B

  • you want the most recent training data — it shipped Mar 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemini 2.0 Flash Thinking
Google
Gemma 3 4B
Google
Core performance indexes
LLM Stats Score
16.7
#220
-1.9
#338
Reasoning
17.0
#213
-2.9
#335
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$0.02 / M
Output price
— / M
$0.04 / M
Context window
—
131,072

Individual benchmarks

3 reported for Gemini 2.0 Flash Thinking · 26 for Gemma 3 4B

1 shared

Gemini 2.0 Flash Thinking outperforms in 1 benchmarks (GPQA), while Gemma 3 4B is better at 0 benchmarks.

Gemini 2.0 Flash Thinking significantly outperforms across most benchmarks.

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Gemma 3 4B specifies input context (131,072 tokens). Only Gemma 3 4B specifies output context (131,072 tokens).

Google
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
Google
Gemma 3 4B
Input131,072 tokens
Output131,072 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 2.0 Flash Thinking and Gemma 3 4B support multimodal inputs.

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

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

Gemma 3 4B

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.0 Flash Thinking is licensed under a proprietary license, while Gemma 3 4B uses Gemma.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 2.0 Flash Thinking

Proprietary

Closed source

Gemma 3 4B

Gemma

Open weights

Release Timeline

When each model was launched

Gemini 2.0 Flash Thinking was released on 2025-01-21, while Gemma 3 4B was released on 2025-03-12.

Gemma 3 4B is 2 months newer than Gemini 2.0 Flash Thinking.

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.7 years ago

Gemma 3 4B

Mar 12, 2025

1.5 years ago

1mo newer

Knowledge Cutoff

When training data ends

Both models have the same knowledge cutoff date of 2024-08-01.

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

Gemini 2.0 Flash Thinking

Aug 2024

Gemma 3 4B

Aug 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 2.0 Flash Thinking and Gemma 3 4B side-by-side, then vote on the output you prefer.

Gemini 2.0 Flash Thinking
✓ Preferred
Gemma 3 4B
Open in Playground

FAQ

Common questions about Gemini 2.0 Flash Thinking vs Gemma 3 4B.

Which is better, Gemini 2.0 Flash Thinking or Gemma 3 4B?

Gemini 2.0 Flash Thinking leads the LLM Stats Score 16.7 to -1.9. Gemini 2.0 Flash Thinking is made by Google and Gemma 3 4B is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 2.0 Flash Thinking compare to Gemma 3 4B in benchmarks?

Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%. Gemma 3 4B scores IFEval: 90.2%, GSM8k: 89.2%, DocVQA: 75.8%, MATH: 75.6%, AI2D: 74.8%.

What are the context window sizes for Gemini 2.0 Flash Thinking and Gemma 3 4B?

Gemini 2.0 Flash Thinking supports an unknown number of tokens and Gemma 3 4B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 2.0 Flash Thinking and Gemma 3 4B?

Key differences include LLM Stats Score (16.7 vs -1.9), licensing (Proprietary vs Gemma). See the full comparison above for benchmark-by-benchmark results.

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