Cheaper, Better, Faster, Stronger | Mistral AI

This post introduces Mixtral 8x22B, a new open-source sparse Mixture-of-Experts (SMoE) model. It highlights the model's cost efficiency (39B active parameters out of 141B total), multilingual fluency (English, French, Italian, German, Spanish), strong mathematics and coding capabilities, native function calling, and a 64K token context window. The post emphasizes its performance-to-cost ratio, claiming it's faster than dense 70B models and more capable than other open-weight models. It includes benchmark comparisons (MMLU, HellaSwag, Wino Grande, Arc Challenge, TriviaQA, NaturalQS, HumanEval, MBPP, GSM8K, Math) demonstrating its superiority in reasoning, knowledge, multilingual tasks, math, and coding against other leading open models like LLaMA 2 70B.