Model Comparison

Gemma 3 4B vs Qwen3 VL 4B Thinking

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Gemma 3 4B is 13.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Gemma 3 4B outperforms in 1 benchmarks (IFEval), while Qwen3 VL 4B Thinking is better at 5 benchmarks (AI2D, GPQA, MathVista-Mini, MMLU-Pro, MMMU (val)).

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.

Tue Apr 28 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 4B costs less

For input processing, Gemma 3 4B ($0.02/1M tokens) is 5.0x cheaper than Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, Gemma 3 4B ($0.04/1M tokens) is 25.0x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, Qwen3 VL 4B Thinking is more expensive than Gemma 3 4B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Tue Apr 28 2026 • llm-stats.com

Gemma 3 4B

Input tokens$0.02

Output tokens$0.04

Best providerDeepinfra

Qwen3 VL 4B Thinking

Input tokens$0.10

Output tokens$1.00

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

0.0M diff

Qwen3 VL 4B Thinking has 0.0B more parameters than Gemma 3 4B, making it 0.0% larger.

Gemma 3 4B

4.0Bparameters

Qwen3 VL 4B Thinking

4.0Bparameters

4.0B

Gemma 3 4B

4.0B

Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to Gemma 3 4B's 131,072 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Gemma 3 4B is limited to 131,072 tokens.

Gemma 3 4B

Input131,072 tokens

Output131,072 tokens

Qwen3 VL 4B Thinking

Input262,144 tokens

Output262,144 tokens

Tue Apr 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 4B and Qwen3 VL 4B Thinking support multimodal inputs.

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

Gemma 3 4B

Text

Images

Audio

Video

Qwen3 VL 4B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Gemma 3 4B 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 3 4B

Gemma

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3 4B was released on 2025-03-12, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 6 months newer than Gemma 3 4B.

Gemma 3 4B

Mar 12, 2025

1.1 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

7 months ago

6mo newer

Knowledge Cutoff

When training data ends

Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while Qwen3 VL 4B Thinking's cutoff date is not specified.

We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.

Gemma 3 4B

Aug 2024

Qwen3 VL 4B Thinking

—

Provider Availability

Gemma 3 4B is available from DeepInfra. Qwen3 VL 4B Thinking is available from DeepInfra.

Gemma 3 4B

Deepinfra

Input Price:Input: $0.02/1MOutput Price:Output: $0.04/1M

Qwen3 VL 4B Thinking

Deepinfra

Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Gemma 3 4B

View details

Google

Less expensive input tokens

Less expensive output tokens

Higher IFEval score (90.2% vs 82.6%)

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher AI2D score (84.9% vs 74.8%)

Higher GPQA score (64.1% vs 30.8%)

Higher MathVista-Mini score (79.5% vs 50.0%)

Higher MMLU-Pro score (73.6% vs 43.6%)

Higher MMMU (val) score (70.8% vs 48.8%)

Detailed Comparison

AI Model Comparison Table
Feature	Gemma 3 4B	Qwen3 VL 4B Thinking

FAQ

Common questions about Gemma 3 4B vs Qwen3 VL 4B Thinking

Qwen3 VL 4B Thinking significantly outperforms across most benchmarks. Gemma 3 4B 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.

Gemma 3 4B scores IFEval: 90.2%, GSM8k: 89.2%, DocVQA: 75.8%, MATH: 75.6%, AI2D: 74.8%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Gemma 3 4B is 5.0x cheaper for input tokens. Gemma 3 4B costs $0.02/M input and $0.04/M output via deepinfra. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra.

Gemma 3 4B supports 131K 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.

Key differences include context window (131K vs 262K), input pricing ($0.02 vs $0.10/M), licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Gemma 3 4B is developed by Google and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.

Gemma 3 4B vs Qwen3 VL 4B Thinking

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

Gemma 3 4B

Qwen3 VL 4B Thinking

License

Release Timeline

Knowledge Cutoff

Provider Availability

Gemma 3 4B

Qwen3 VL 4B Thinking

Outputs Comparison

Key Takeaways

Gemma 3 4B

Qwen3 VL 4B Thinking

Detailed Comparison

FAQ

Which is better, Gemma 3 4B or Qwen3 VL 4B Thinking?

How does Gemma 3 4B compare to Qwen3 VL 4B Thinking in benchmarks?

Is Gemma 3 4B cheaper than Qwen3 VL 4B Thinking?

What are the context window sizes for Gemma 3 4B and Qwen3 VL 4B Thinking?

What are the main differences between Gemma 3 4B and Qwen3 VL 4B Thinking?

Who makes Gemma 3 4B and Qwen3 VL 4B Thinking?