Comprehensive side-by-side LLM comparison
Llama 4 Scout leads with 58.0% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than Devstral Small 1.1. Both models have similar pricing. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, Llama 4 Scout is the stronger choice for coding tasks.
Mistral AI
Devstral Small 1.1 is a language model developed by Mistral AI. The model shows competitive results across 1 benchmarks. Notable strengths include SWE-Bench Verified (53.6%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Mistral AI'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.
3 months newer
Llama 4 Scout
Meta
2025-04-05
Devstral Small 1.1
Mistral AI
2025-07-11
Cost per million tokens (USD)
Devstral Small 1.1
Llama 4 Scout
Context window and performance specifications
Average performance across 13 common benchmarks
Devstral Small 1.1
Llama 4 Scout
Available providers and their performance metrics
Devstral Small 1.1
Mistral AI
Llama 4 Scout
Devstral Small 1.1
Llama 4 Scout
Devstral Small 1.1
Llama 4 Scout
DeepInfra
Fireworks
Groq
Lambda
Novita
Together