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Model Comparison

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

Google

Gemma 3n E4B Instructed LiteRT Preview

Google

Gemma 3n E4B Instructed LiteRT Preview is a multimodal language model developed by Google. The model shows competitive results across 28 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.

Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507 is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 69.2% across 25 benchmarks. It excels particularly in MMLU-Redux (93.8%), AIME25 (92.3%), WritingBench (88.3%). It supports a 387K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.

Google

Gemma 3n E4B Instructed LiteRT Preview

Google

2025-05-20

Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

Alibaba Cloud / Qwen Team

2025-07-25

2 months newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E4B Instructed LiteRT Preview

Max Context:-
Parameters:1.9B
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

Larger context
Max Context:387.1K
Parameters:235.0B

Average performance across 4 common benchmarks

Google

Gemma 3n E4B Instructed LiteRT Preview

Average Score:37.9%
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

+44.0%
Average Score:81.9%

Performance comparison across key benchmark categories

Google

Gemma 3n E4B Instructed LiteRT Preview

general
50.7%
reasoning
+8.5%
73.4%
math
36.7%
code
38.9%
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

general
+26.7%
77.4%
reasoning
64.9%
math
+23.4%
60.1%
code
+15.1%
53.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B Instructed LiteRT Preview

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3n E4B Instructed LiteRT Preview

0 providers
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

1 providers

Novita

Google

Gemma 3n E4B Instructed LiteRT Preview

Avg Score:37.9%
Providers:0
Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507

+44.0%
Avg Score:81.9%
Providers:1