Comprehensive side-by-side LLM comparison
Llama 4 Scout leads with 1.9% higher average benchmark score. Llama 4 Scout offers 18.9M more tokens in context window than Gemini 2.0 Flash-Lite. Both models have similar pricing. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
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.
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%). 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.
1 month newer
Gemini 2.0 Flash-Lite
2025-02-05
Llama 4 Scout
Meta
2025-04-05
Cost per million tokens (USD)
Gemini 2.0 Flash-Lite
Llama 4 Scout
Context window and performance specifications
Average performance across 21 common benchmarks
Gemini 2.0 Flash-Lite
Llama 4 Scout
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics
Gemini 2.0 Flash-Lite
Llama 4 Scout
Gemini 2.0 Flash-Lite
Llama 4 Scout
Gemini 2.0 Flash-Lite
Llama 4 Scout
DeepInfra
Fireworks
Groq
Lambda
Novita
Together