Model Comparison

Gemma 3n E4B Instructed LiteRT Preview vs Qwen3 VL 4B ThinkingWhich is better in 2026?

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.

Verdict: Gemma 3n E4B Instructed LiteRT Preview vs Qwen3 VL 4B Thinking — which is better?

Gemma 3n E4B Instructed LiteRT Preview (by Google) and Qwen3 VL 4B Thinking (by Alibaba Cloud / Qwen Team) 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 3n E4B Instructed LiteRT Preview outperforms in 0 benchmarks, while Qwen3 VL 4B Thinking is better at 6 benchmarks (AIME 2025, GPQA, Include, MMLU, MMLU-Pro, MMLU-ProX). Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.

Choose Gemma 3n E4B Instructed LiteRT Preview if…

  • you are already invested in the Google ecosystem

Choose Qwen3 VL 4B Thinking if…

  • you want the strongest raw capability — it leads on 6 of 6 shared benchmarks
  • you want the most recent training data — it shipped Sep 2025
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Gemma 3n E4B Instructed LiteRT Preview outperforms in 0 benchmarks, while Qwen3 VL 4B Thinking is better at 6 benchmarks (AIME 2025, GPQA, Include, MMLU, MMLU-Pro, MMLU-ProX).

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.

Wed Jun 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

2.1B diff

Qwen3 VL 4B Thinking has 2.1B more parameters than Gemma 3n E4B Instructed LiteRT Preview, making it 109.4% larger.

Google
Gemma 3n E4B Instructed LiteRT Preview
1.9Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
1.9B
Gemma 3n E4B Instructed LiteRT Preview
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).

Google
Gemma 3n E4B Instructed LiteRT Preview
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Wed Jun 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3n E4B Instructed LiteRT Preview and Qwen3 VL 4B Thinking support multimodal inputs.

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

Gemma 3n E4B Instructed LiteRT Preview

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B Instructed LiteRT Preview is licensed under Gemma, while Qwen3 VL 4B Thinking uses Apache 2.0.

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

Gemma 3n E4B Instructed LiteRT Preview

Gemma

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B Instructed LiteRT Preview was released on 2025-05-20, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 4 months newer than Gemma 3n E4B Instructed LiteRT Preview.

Gemma 3n E4B Instructed LiteRT Preview

May 20, 2025

1.1 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

9 months ago

4mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed LiteRT Preview has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 4B Thinking's cutoff date is not specified.

We can confirm Gemma 3n E4B Instructed LiteRT Preview's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.

Gemma 3n E4B Instructed LiteRT Preview

Jun 2024

Qwen3 VL 4B Thinking

—

Outputs Comparison

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Key Takeaways

Google

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

Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Higher AIME 2025 score (74.5% vs 11.6%)
Higher GPQA score (64.1% vs 23.7%)
Higher Include score (64.6% vs 57.2%)
Higher MMLU score (81.5% vs 64.9%)
Higher MMLU-Pro score (73.6% vs 50.6%)
Higher MMLU-ProX score (65.0% vs 19.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B Instructed LiteRT Preview
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking

FAQ

Common questions about Gemma 3n E4B Instructed LiteRT Preview vs Qwen3 VL 4B Thinking.

Which is better, Gemma 3n E4B Instructed LiteRT Preview or Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Gemma 3n E4B Instructed LiteRT Preview is made by Google and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 3n E4B Instructed LiteRT Preview compare to Qwen3 VL 4B Thinking in benchmarks?

Gemma 3n E4B Instructed LiteRT Preview scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, HumanEval: 75.0%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

What are the context window sizes for Gemma 3n E4B Instructed LiteRT Preview and Qwen3 VL 4B Thinking?

Gemma 3n E4B Instructed LiteRT Preview supports an unknown number of tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 3n E4B Instructed LiteRT Preview and Qwen3 VL 4B Thinking?

Key differences include licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3n E4B Instructed LiteRT Preview and Qwen3 VL 4B Thinking?

Gemma 3n E4B Instructed LiteRT Preview is developed by Google and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.

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