Llama 4 Maverick vs Mistral Large: Open-Source LLMs Compared in 2026
Compare Meta Llama 4 Maverick and Mistral Large on performance, licensing, context window and cost. Discover which open-source AI model best fits your project.
Llama 4 Maverick outperforms Mistral Large on virtually all benchmarks thanks to the MoE architecture with 402B parameters. The 1M token context window and more permissive license make it the stronger choice for most applications. Mistral Large retains value for European organizations requiring an EU-based provider where 128K context is sufficient.
Llama 4 Maverick
Meta's latest open-source model with 402B total parameters of which only 17B are active per token (Mixture of Experts). Llama 4 Maverick offers a 1M token context window, native image processing and achieves 69.8% on GPQA Diamond and 80.5% on MMLU-Pro.
Mistral Large
The flagship model from European Mistral AI with 123B parameters and a 128K token context window. Mistral Large positions itself as the European alternative with strong multilingual capabilities and compliance-focused features for enterprise use.
What are the key differences between Llama 4 Maverick and Mistral Large?
| Feature | Llama 4 Maverick | Mistral Large |
|---|---|---|
| Parameters & architecture | 402B total, 17B active per token (MoE); enormous capacity with limited compute | 123B dense transformer; full model active for every inference |
| Context window | 1M tokens; processes entire repositories and long-running conversations | 128K tokens; suitable for most business documents |
| Benchmarks | 69.8% GPQA Diamond, 80.5% MMLU-Pro; significantly stronger on reasoning | 24.94% GPQA Diamond, 50.69% MMLU-Pro; solid but lower scoring |
| Multimodal | Native image processing (image input); multimodal without extra modules | Text only; no native image or audio input |
| License | Meta Community License; unrestricted commercial use without MAU limit | Mistral Research License; commercial use requires paid license |
What is the verdict on Llama 4 Maverick vs Mistral Large?
Llama 4 Maverick outperforms Mistral Large on virtually all benchmarks thanks to the MoE architecture with 402B parameters. The 1M token context window and more permissive license make it the stronger choice for most applications. Mistral Large retains value for European organizations requiring an EU-based provider where 128K context is sufficient.
Which option does MG Software recommend?
At MG Software, we choose Llama 4 Maverick as our default open-source model for local development and production applications not requiring a closed-source API. The combination of frontier performance, 1M context window and free commercial license is unmatched. We recommend Mistral Large specifically to clients with EU compliance requirements needing a European provider.
Frequently asked questions
Related articles
DeepSeek R1 vs Claude Opus 4.6: Budget AI vs Frontier Coding in 2026
Compare DeepSeek R1 and Claude Opus 4.6 on architecture, pricing, benchmarks and coding performance. Discover whether the open-source R1 model can compete with Anthropic's premium model.
DeepSeek R1 vs GPT-5.3: Open-Source Challenger vs OpenAI's Top Model
Compare DeepSeek R1 and GPT-5.3 on architecture, context window, pricing, reasoning and coding. Discover whether the budget-friendly R1 model measures up to GPT-5.3.
Llama 4 Maverick vs DeepSeek R1: The Two Open-Source Giants Compared
Compare Llama 4 Maverick and DeepSeek R1 on architecture, license, context window and performance. Discover which open-source AI model best fits your project in 2026.
Best Open Source LLMs 2026 - Top 5 Compared
Compare the best open source large language models of 2026. From Llama 4 to DeepSeek R1 — discover which open model fits your AI project.