Model Comparison

Gemma 3 4B vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Gemma 3 4B is 48.4x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Gemma 3 4B outperforms in 1 benchmarks (IFEval), while Qwen3 VL 235B A22B Thinking is better at 4 benchmarks (AI2D, MathVista-Mini, MMLU-Pro, SimpleQA).

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

Mon Jun 01 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 22.5x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).

For output processing, Gemma 3 4B ($0.04/1M tokens) is 87.3x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).

In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than Gemma 3 4B.*

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

Lowest available price from all providers
Mon Jun 01 2026 • llm-stats.com
Google
Gemma 3 4B
Input tokens$0.02
Output tokens$0.04
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input tokens$0.45
Output tokens$3.49
Best providerDeepinfra
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Model Size

Parameter count comparison

232.0B diff

Qwen3 VL 235B A22B Thinking has 232.0B more parameters than Gemma 3 4B, making it 5800.0% larger.

Google
Gemma 3 4B
4.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
4.0B
Gemma 3 4B
236.0B
Qwen3 VL 235B A22B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to Gemma 3 4B's 131,072 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while Gemma 3 4B is limited to 131,072 tokens.

Google
Gemma 3 4B
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Jun 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 4B and Qwen3 VL 235B A22B 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 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3 4B is licensed under Gemma, while Qwen3 VL 235B A22B 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 235B A22B 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 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 6 months newer than Gemma 3 4B.

Gemma 3 4B

Mar 12, 2025

1.2 years ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

8 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 235B A22B 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 235B A22B Thinking's cutoff date.

Gemma 3 4B

Aug 2024

Qwen3 VL 235B A22B Thinking

Provider Availability

Gemma 3 4B is available from DeepInfra. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.

Gemma 3 4B

deepinfra logo
Deepinfra
Input Price:Input: $0.02/1MOutput Price:Output: $0.04/1M

Qwen3 VL 235B A22B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.45/1MOutput Price:Output: $3.49/1M
novita logo
Novita
Input Price:Input: $0.98/1MOutput Price:Output: $3.95/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive input tokens
Less expensive output tokens
Higher IFEval score (90.2% vs 88.2%)
Larger context window (262,144 tokens)
Higher AI2D score (89.2% vs 74.8%)
Higher MathVista-Mini score (85.8% vs 50.0%)
Higher MMLU-Pro score (83.8% vs 43.6%)
Higher SimpleQA score (44.4% vs 4.0%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3 4B
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking

FAQ

Common questions about Gemma 3 4B vs Qwen3 VL 235B A22B Thinking.

Which is better, Gemma 3 4B or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Gemma 3 4B is made by Google and Qwen3 VL 235B A22B 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 4B compare to Qwen3 VL 235B A22B Thinking in benchmarks?

Gemma 3 4B scores IFEval: 90.2%, GSM8k: 89.2%, DocVQA: 75.8%, MATH: 75.6%, AI2D: 74.8%. Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.

Is Gemma 3 4B cheaper than Qwen3 VL 235B A22B Thinking?

Gemma 3 4B is 22.5x cheaper for input tokens. Gemma 3 4B costs $0.02/M input and $0.04/M output via deepinfra. Qwen3 VL 235B A22B Thinking costs $0.45/M input and $3.49/M output via deepinfra.

What are the context window sizes for Gemma 3 4B and Qwen3 VL 235B A22B Thinking?

Gemma 3 4B supports 131K tokens and Qwen3 VL 235B A22B 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 4B and Qwen3 VL 235B A22B Thinking?

Key differences include context window (131K vs 262K), input pricing ($0.02 vs $0.45/M), licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 4B and Qwen3 VL 235B A22B Thinking?

Gemma 3 4B is developed by Google and Qwen3 VL 235B A22B Thinking is developed by Alibaba Cloud / Qwen Team.