Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Gemma 3n E2B Instructed

Google

Gemma 3n E2B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (66.5%), MMLU (60.1%), Global-MMLU-Lite (59.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

Qwen3-235B-A22B-Instruct-2507

Alibaba

Qwen3-235B-A22B-Instruct-2507 is a language model developed by Alibaba. It achieves strong performance with an average score of 72.1% across 25 benchmarks. It excels particularly in ZebraLogic (95.0%), MMLU-Redux (93.1%), IFEval (88.7%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Gemma 3n E2B Instructed

Google

2025-06-26

Qwen3-235B-A22B-Instruct-2507

Alibaba

2025-07-22

26 days newer

Average performance across 4 common benchmarks

Gemma 3n E2B Instructed

Average Score:28.0%

Qwen3-235B-A22B-Instruct-2507

+51.8%

Average Score:79.8%

Performance comparison across key benchmark categories

Gemma 3n E2B Instructed

general

32.8%

code

33.2%

math

40.4%

Qwen3-235B-A22B-Instruct-2507

general

+40.9%

73.7%

code

+37.1%

70.3%

math

+9.8%

50.2%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

Gemma 3n E2B Instructed

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Gemma 3n E2B Instructed

0 providers

Qwen3-235B-A22B-Instruct-2507

0 providers

Gemma 3n E2B Instructed

Avg Score:28.0%

Providers:0

Qwen3-235B-A22B-Instruct-2507

+51.8%

Avg Score:79.8%

Providers:0