Model Comparison

Gemma 3n E2B Instructed LiteRT (Preview) vs Qwen3-235B-A22B-Thinking-2507Which is better in 2026?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Verdict: Gemma 3n E2B Instructed LiteRT (Preview) vs Qwen3-235B-A22B-Thinking-2507 — which is better?

Gemma 3n E2B Instructed LiteRT (Preview) (by Google) and Qwen3-235B-A22B-Thinking-2507 (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 E2B Instructed LiteRT (Preview) outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 5 benchmarks (AIME 2025, GPQA, Include, MMLU-Pro, MMLU-ProX). Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Choose Gemma 3n E2B Instructed LiteRT (Preview) if…

  • you are already invested in the Google ecosystem

Choose Qwen3-235B-A22B-Thinking-2507 if…

  • you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
  • you want the most recent training data — it shipped Jul 2025

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Gemma 3n E2B Instructed LiteRT (Preview) outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 5 benchmarks (AIME 2025, GPQA, Include, MMLU-Pro, MMLU-ProX).

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Tue Jul 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

233.1B diff

Qwen3-235B-A22B-Thinking-2507 has 233.1B more parameters than Gemma 3n E2B Instructed LiteRT (Preview), making it 12203.7% larger.

Google
Gemma 3n E2B Instructed LiteRT (Preview)
1.9Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
235.0Bparameters
1.9B
Gemma 3n E2B Instructed LiteRT (Preview)
235.0B
Qwen3-235B-A22B-Thinking-2507

Context Window

Maximum input and output token capacity

Only Qwen3-235B-A22B-Thinking-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Thinking-2507 specifies output context (131,072 tokens).

Google
Gemma 3n E2B Instructed LiteRT (Preview)
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Tue Jul 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B Instructed LiteRT (Preview) supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.

Gemma 3n E2B Instructed LiteRT (Preview) can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E2B Instructed LiteRT (Preview)

Text
Images
Audio
Video

Qwen3-235B-A22B-Thinking-2507

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E2B Instructed LiteRT (Preview) is licensed under Gemma, while Qwen3-235B-A22B-Thinking-2507 uses Apache 2.0.

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

Gemma 3n E2B Instructed LiteRT (Preview)

Gemma

Open weights

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E2B Instructed LiteRT (Preview) was released on 2025-05-20, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

Qwen3-235B-A22B-Thinking-2507 is 2 months newer than Gemma 3n E2B Instructed LiteRT (Preview).

Gemma 3n E2B Instructed LiteRT (Preview)

May 20, 2025

1.2 years ago

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

11 months ago

2mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed LiteRT (Preview) has a documented knowledge cutoff of 2024-06-01, while Qwen3-235B-A22B-Thinking-2507's cutoff date is not specified.

We can confirm Gemma 3n E2B Instructed LiteRT (Preview)'s training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3-235B-A22B-Thinking-2507's cutoff date.

Gemma 3n E2B Instructed LiteRT (Preview)

Jun 2024

Qwen3-235B-A22B-Thinking-2507

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Supports multimodal inputs
Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)
Higher AIME 2025 score (92.3% vs 6.7%)
Higher GPQA score (81.1% vs 24.8%)
Higher Include score (81.0% vs 38.6%)
Higher MMLU-Pro score (84.4% vs 40.5%)
Higher MMLU-ProX score (81.0% vs 8.1%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemma 3n E2B Instructed LiteRT (Preview) and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.

Gemma 3n E2B Instructed LiteRT (Preview)
✓ Preferred
Qwen3-235B-A22B-Thinking-2507
Open in Playground
AI Model Comparison Table
Feature
Google
Gemma 3n E2B Instructed LiteRT (Preview)
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507

FAQ

Common questions about Gemma 3n E2B Instructed LiteRT (Preview) vs Qwen3-235B-A22B-Thinking-2507.

Which is better, Gemma 3n E2B Instructed LiteRT (Preview) or Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Gemma 3n E2B Instructed LiteRT (Preview) is made by Google and Qwen3-235B-A22B-Thinking-2507 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 E2B Instructed LiteRT (Preview) compare to Qwen3-235B-A22B-Thinking-2507 in benchmarks?

Gemma 3n E2B Instructed LiteRT (Preview) scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

What are the context window sizes for Gemma 3n E2B Instructed LiteRT (Preview) and Qwen3-235B-A22B-Thinking-2507?

Gemma 3n E2B Instructed LiteRT (Preview) supports an unknown number of tokens and Qwen3-235B-A22B-Thinking-2507 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 E2B Instructed LiteRT (Preview) and Qwen3-235B-A22B-Thinking-2507?

Key differences include multimodal support (yes vs no), licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3n E2B Instructed LiteRT (Preview) and Qwen3-235B-A22B-Thinking-2507?

Gemma 3n E2B Instructed LiteRT (Preview) is developed by Google and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

Related comparisons