Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 5.1% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than DeepSeek-V3.1. Llama 4 Scout is $0.89 cheaper per million tokens. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek'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.
2 months newer
DeepSeek-V3.1
DeepSeek
2025-01-10
Llama 4 Scout
Meta
2025-04-05
Cost per million tokens (USD)
DeepSeek-V3.1
Llama 4 Scout
Context window and performance specifications
Average performance across 25 common benchmarks
DeepSeek-V3.1
Llama 4 Scout
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Llama 4 Scout
DeepSeek-V3.1
Llama 4 Scout
DeepSeek-V3.1
Llama 4 Scout
DeepInfra
Fireworks
Groq
Lambda
Novita
Together