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

Gemma 3 4B
Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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.

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 3 4B
2025-03-12

Qwen3-235B-A22B-Instruct-2507
Alibaba
2025-07-22
4 months newer
Performance Metrics
Context window and performance specifications

Gemma 3 4B

Qwen3-235B-A22B-Instruct-2507
Average performance across 4 common benchmarks

Gemma 3 4B

Qwen3-235B-A22B-Instruct-2507
Performance comparison across key benchmark categories

Gemma 3 4B

Qwen3-235B-A22B-Instruct-2507
Gemma 3 4B
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3 4B
DeepInfra

Qwen3-235B-A22B-Instruct-2507

Gemma 3 4B

Qwen3-235B-A22B-Instruct-2507