Three publisher flagships with almost nothing in common beyond their billing tier. Mistral Large 2 is a 123B-parameter dense model released July 2024 by France-based Mistral AI, built around European multilingual quality, structured output reliability, and tight integration with Mistral's managed API. Function calling and JSON mode are first-class. The 128K context window is matched by few rivals at this price point. The Mistral Research License restricts self-hosted commercial use, so production workloads generally go through Mistral's own API or require an enterprise agreement. Nemotron-4 340B Instruct is NVIDIA's flagship open release, a dense 340-billion-parameter model released June 2024. Its design purpose is synthetic training data generation rather than general-purpose chat — NVIDIA explicitly positioned it as a reference model for producing diverse, high-quality instruction datasets for fine-tuning smaller models. The 4K context ceiling is a hard constraint that rules it out for most document-processing and RAG use cases. Hosting concentrates on NVIDIA's NIM service, and the NVIDIA Open Model License is not OSI-approved. If you are not building synthetic data pipelines, the cost-to-benefit is difficult to justify. Qwen 3 72B Instruct is Alibaba's April 2025 flagship open model at 72 billion parameters, inheriting a 131K context window and adding meaningfully improved multilingual coverage across CJK, Arabic, and European languages over its 2.5-series predecessor. Benchmark performance is competitive with Mistral Large 2 on most English-language tasks and surpasses it on multilingual evals. Pick Mistral Large 2 for European-language enterprise workloads with managed API support. Pick Nemotron-4 340B only for synthetic data generation at scale. Pick Qwen 3 72B as the cost-effective option when multilingual breadth and long-context support are both required.