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.

Llama 4 Scout
Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). The model shows particular specialization in vision tasks with an average performance of 81.9%. With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.

Gemma 3 4B
2025-03-12

Llama 4 Scout
Meta
2025-04-05
24 days newer
Pricing Comparison
Cost per million tokens (USD)

Gemma 3 4B

Llama 4 Scout
Performance Metrics
Context window and performance specifications

Gemma 3 4B

Llama 4 Scout
Average performance across 7 common benchmarks

Gemma 3 4B

Llama 4 Scout
Performance comparison across key benchmark categories

Gemma 3 4B

Llama 4 Scout
Gemma 3 4B
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3 4B
DeepInfra

Llama 4 Scout
Together
DeepInfra
Fireworks
Groq
Novita
Lambda

Gemma 3 4B

Llama 4 Scout