A full reasoning-oriented MoE, a cost-efficient dense model, and a managed multilingual flagship. DeepSeek R1 is a 671B-parameter MoE from DeepSeek, released January 2025, trained specifically to surface chain-of-thought reasoning traces. On AIME 2024 and MATH evaluations it scores in the same range as frontier proprietary models, which was notable at the time. Context window reaches 128K. The DeepSeek license permits commercial use with conditions, and hosting is available on DeepInfra, Fireworks, and the DeepSeek API directly. If you are building a math tutor, code reasoning agent, or any pipeline where explicit reasoning steps are an output requirement, this is the correct tier. Llama 3.3 70B Instruct is Meta's December 2024 70B dense model, 131K context, Llama 3 community license. It is not a reasoning-specialist: instruction-following, document summarization, and open-ended generation are its strengths. Its main advantages are cost — running 70B is materially cheaper than 671B MoE at similar output quality for general tasks — and the breadth of providers that host it. For workloads where chain-of-thought is not essential, the 70B option often wins on total cost. Mistral Large 2 sits at 123B parameters with a 128K context window and Mistral's Research License. It outperforms Llama 3.3 70B on European multilingual tasks and structured output reliability, and it offers a polished function-calling API through Mistral's managed endpoint. Pick DeepSeek R1 for reasoning-heavy pipelines where quality ceiling and trace visibility matter most. Pick Llama 3.3 70B for general-purpose workloads with a tight cost budget and clean licensing needs. Pick Mistral Large 2 for multilingual European production deployments with managed API support.