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

Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). 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 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.

Gemini 2.0 Flash-Lite
2025-02-05

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

Gemini 2.0 Flash-Lite

Llama 4 Scout
Performance Metrics
Context window and performance specifications

Gemini 2.0 Flash-Lite

Llama 4 Scout
Average performance across 4 common benchmarks

Gemini 2.0 Flash-Lite

Llama 4 Scout
Performance comparison across key benchmark categories

Gemini 2.0 Flash-Lite

Llama 4 Scout
Gemini 2.0 Flash-Lite
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.0 Flash-Lite

Llama 4 Scout
Together
DeepInfra
Fireworks
Groq
Novita
Lambda

Gemini 2.0 Flash-Lite

Llama 4 Scout