Model Comparison

Gemma 3 1B vs Qwen3 VL 8B Thinking

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemma 3 1B outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 4 benchmarks (GPQA, IFEval, MMLU-Pro, SimpleQA).

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Sun May 31 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

8.0B diff

Qwen3 VL 8B Thinking has 8.0B more parameters than Gemma 3 1B, making it 800.0% larger.

Gemma 3 1B

1.0Bparameters

Qwen3 VL 8B Thinking

9.0Bparameters

1.0B

Gemma 3 1B

9.0B

Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 8B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 8B Thinking specifies output context (262,144 tokens).

Gemma 3 1B

Input- tokens

Output- tokens

Qwen3 VL 8B Thinking

Input262,144 tokens

Output262,144 tokens

Sun May 31 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 8B Thinking supports multimodal inputs, whereas Gemma 3 1B does not.

Qwen3 VL 8B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3 1B

Text

Images

Audio

Video

Qwen3 VL 8B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Gemma 3 1B is licensed under Gemma, while Qwen3 VL 8B Thinking uses Apache 2.0.

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

Gemma 3 1B

Gemma

Open weights

Qwen3 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3 1B was released on 2025-03-12, while Qwen3 VL 8B Thinking was released on 2025-09-22.

Qwen3 VL 8B Thinking is 6 months newer than Gemma 3 1B.

Gemma 3 1B

Mar 12, 2025

1.2 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

8 months ago

6mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Gemma 3 1B

View details

Google

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

Qwen3 VL 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Supports multimodal inputs

Higher GPQA score (69.9% vs 19.2%)

Higher IFEval score (83.2% vs 80.2%)

Higher MMLU-Pro score (77.3% vs 14.7%)

Higher SimpleQA score (49.6% vs 2.2%)

Detailed Comparison

AI Model Comparison Table
Feature	Gemma 3 1B	Qwen3 VL 8B Thinking

FAQ

Common questions about Gemma 3 1B vs Qwen3 VL 8B Thinking.

Which is better, Gemma 3 1B or Qwen3 VL 8B Thinking?

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Gemma 3 1B is made by Google and Qwen3 VL 8B 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 3 1B compare to Qwen3 VL 8B Thinking in benchmarks?

Gemma 3 1B scores IFEval: 80.2%, GSM8k: 62.8%, Natural2Code: 56.0%, MATH: 48.0%, HumanEval: 41.5%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

What are the context window sizes for Gemma 3 1B and Qwen3 VL 8B Thinking?

Gemma 3 1B supports an unknown number of tokens and Qwen3 VL 8B 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 3 1B and Qwen3 VL 8B Thinking?

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

Who makes Gemma 3 1B and Qwen3 VL 8B Thinking?

Gemma 3 1B is developed by Google and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.