Model Comparison

Gemma 3 12B vs Qwen3 VL 8B Thinking

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Gemma 3 12B is 10.5x cheaper per token.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Gemma 3 12B outperforms in 1 benchmarks (IFEval), while Qwen3 VL 8B Thinking is better at 6 benchmarks (AI2D, GPQA, MathVista-Mini, MMLU-Pro, MMMU (val), SimpleQA).

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Sun May 10 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 12B costs less

For input processing, Gemma 3 12B ($0.05/1M tokens) is 3.6x cheaper than Qwen3 VL 8B Thinking ($0.18/1M tokens).

For output processing, Gemma 3 12B ($0.10/1M tokens) is 20.9x cheaper than Qwen3 VL 8B Thinking ($2.09/1M tokens).

In conclusion, Qwen3 VL 8B Thinking is more expensive than Gemma 3 12B.*

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

Lowest available price from all providers

Sun May 10 2026 • llm-stats.com

Gemma 3 12B

Input tokens$0.05

Output tokens$0.10

Best providerDeepinfra

Qwen3 VL 8B Thinking

Input tokens$0.18

Output tokens$2.09

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

3.0B diff

Gemma 3 12B has 3.0B more parameters than Qwen3 VL 8B Thinking, making it 33.3% larger.

Gemma 3 12B

12.0Bparameters

Qwen3 VL 8B Thinking

9.0Bparameters

12.0B

Gemma 3 12B

9.0B

Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 8B Thinking accepts 262,144 input tokens compared to Gemma 3 12B's 131,072 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 tokens, while Gemma 3 12B is limited to 131,072 tokens.

Gemma 3 12B

Input131,072 tokens

Output131,072 tokens

Qwen3 VL 8B Thinking

Input262,144 tokens

Output262,144 tokens

Sun May 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 12B and Qwen3 VL 8B Thinking support multimodal inputs.

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

Gemma 3 12B

Text

Images

Audio

Video

Qwen3 VL 8B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Gemma 3 12B 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 12B

Gemma

Open weights

Qwen3 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3 12B 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 12B.

Gemma 3 12B

Mar 12, 2025

1.2 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

7 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

Provider Availability

Gemma 3 12B is available from DeepInfra. Qwen3 VL 8B Thinking is available from DeepInfra.

Gemma 3 12B

Deepinfra

Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M

Qwen3 VL 8B Thinking

Deepinfra

Input Price:Input: $0.18/1MOutput Price:Output: $2.09/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Gemma 3 12B

View details

Google

Less expensive input tokens

Less expensive output tokens

Higher IFEval score (88.9% vs 83.2%)

Qwen3 VL 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher AI2D score (84.9% vs 84.2%)

Higher GPQA score (69.9% vs 40.9%)

Higher MathVista-Mini score (81.4% vs 62.9%)

Higher MMLU-Pro score (77.3% vs 60.6%)

Higher MMMU (val) score (74.1% vs 59.6%)

Higher SimpleQA score (49.6% vs 6.3%)

Detailed Comparison

AI Model Comparison Table
Feature	Gemma 3 12B	Qwen3 VL 8B Thinking

FAQ

Common questions about Gemma 3 12B vs Qwen3 VL 8B Thinking.

Which is better, Gemma 3 12B or Qwen3 VL 8B Thinking?

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Gemma 3 12B 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 12B compare to Qwen3 VL 8B Thinking in benchmarks?

Gemma 3 12B scores GSM8k: 94.4%, IFEval: 88.9%, DocVQA: 87.1%, BIG-Bench Hard: 85.7%, HumanEval: 85.4%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

Is Gemma 3 12B cheaper than Qwen3 VL 8B Thinking?

Gemma 3 12B is 3.6x cheaper for input tokens. Gemma 3 12B costs $0.05/M input and $0.10/M output via deepinfra. Qwen3 VL 8B Thinking costs $0.18/M input and $2.09/M output via deepinfra.

What are the context window sizes for Gemma 3 12B and Qwen3 VL 8B Thinking?

Gemma 3 12B supports 131K 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 12B and Qwen3 VL 8B Thinking?

Key differences include context window (131K vs 262K), input pricing ($0.05 vs $0.18/M), licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 12B and Qwen3 VL 8B Thinking?

Gemma 3 12B is developed by Google and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.