Gemma 3 12B vs Qwen3 VL 30B A3B Thinking
Qwen3 VL 30B A3B Thinking leads the LLM Stats Score 18.3 to 5.7. Gemma 3 12B is 6.4x cheaper per token.
Google · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 30B A3B Thinking leads the overall LLM Stats Score 18.3 to 5.7, ranking #202 overall.
In the 7 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 12B is roughly 6.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemma 3 12B
- cost matters — it's about 6.4x cheaper per token
Choose Qwen3 VL 30B A3B Thinking
- overall performance matters — it scores 18.3 and ranks #202 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 7 exact shared results
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
26 reported for Gemma 3 12B · 50 for Qwen3 VL 30B A3B Thinking
Gemma 3 12B outperforms in 1 benchmarks (IFEval), while Qwen3 VL 30B A3B Thinking is better at 6 benchmarks (AI2D, GPQA, MathVista-Mini, MMLU-Pro, MMMU (val), SimpleQA).
Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3 12B ($0.05/1M tokens) is 4.0x cheaper than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, Gemma 3 12B ($0.10/1M tokens) is 9.9x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, Qwen3 VL 30B A3B Thinking is more expensive than Gemma 3 12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 30B A3B Thinking has 19.0B more parameters than Gemma 3 12B, making it 158.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. Gemma 3 12B can generate longer responses up to 131,072 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 3 12B and Qwen3 VL 30B A3B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 12B
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Gemma 3 12B is licensed under Gemma, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemma 3 12B was released on 2025-03-12, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Qwen3 VL 30B A3B Thinking is 6 months newer than Gemma 3 12B.
Mar 12, 2025
1.5 years ago
Sep 22, 2025
11 months ago
6mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Gemma 3 12B is available from DeepInfra. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
Gemma 3 12B
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 12B and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 12B vs Qwen3 VL 30B A3B Thinking.