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

Gemma 3 27B
Gemma 3 27B is a multimodal language model developed by Google. It achieves strong performance with an average score of 65.4% across 26 benchmarks. It excels particularly in GSM8k (95.9%), IFEval (90.4%), MATH (89.0%). The model shows particular specialization in math tasks with an average performance of 78.2%. It supports a 262K token context window for handling large documents. The model is available through 2 API providers. 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.

GPT-4.1 nano
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

Gemma 3 27B
2025-03-12

GPT-4.1 nano
OpenAI
2025-04-14
1 month newer
Pricing Comparison
Cost per million tokens (USD)

Gemma 3 27B

GPT-4.1 nano
Performance Metrics
Context window and performance specifications

Gemma 3 27B

GPT-4.1 nano
Average performance across 2 common benchmarks

Gemma 3 27B

GPT-4.1 nano
Performance comparison across key benchmark categories

Gemma 3 27B

GPT-4.1 nano
GPT-4.1 nano
2024-05-31
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3 27B
DeepInfra
Novita

GPT-4.1 nano
OpenAI

Gemma 3 27B

GPT-4.1 nano