Gemma 3n E2B Instructed vs Qwen3 VL 30B A3B Thinking
Qwen3 VL 30B A3B Thinking leads the LLM Stats Score 18.3 to -10.4.
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 -10.4, ranking #202 overall.
In the 6 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemma 3n E2B Instructed
- you are already invested in the Google ecosystem
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 6 exact shared results
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for Gemma 3n E2B Instructed · 50 for Qwen3 VL 30B A3B Thinking
Gemma 3n E2B Instructed outperforms in 0 benchmarks, while Qwen3 VL 30B A3B Thinking is better at 6 benchmarks (AIME 2025, GPQA, Include, MMLU, MMLU-Pro, MMLU-ProX).
Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 30B A3B Thinking has 23.0B more parameters than Gemma 3n E2B Instructed, making it 287.5% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 30B A3B Thinking specifies input context (131,072 tokens). Only Qwen3 VL 30B A3B Thinking specifies output context (32,768 tokens).
Input capabilities
Documented input modalities across available providers
Both Gemma 3n E2B Instructed and Qwen3 VL 30B A3B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3n E2B Instructed
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Gemma 3n E2B Instructed is licensed under a proprietary license, 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.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemma 3n E2B Instructed was released on 2025-06-26, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Qwen3 VL 30B A3B Thinking is 3 months newer than Gemma 3n E2B Instructed.
Jun 26, 2025
1.2 years ago
Sep 22, 2025
11 months ago
2mo newerKnowledge Cutoff
When training data ends
Gemma 3n E2B Instructed has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 30B A3B Thinking's cutoff date is not specified.
We can confirm Gemma 3n E2B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 30B A3B Thinking's cutoff date.
Jun 2024
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Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3n E2B Instructed and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3n E2B Instructed vs Qwen3 VL 30B A3B Thinking.