Charlie Dai, vice president and principal analyst at Forrester, also noted that Mistral LLM-2’s advanced features in code generation, mathematics, reasoning, performance, and cost-effectiveness (designed to run efficiently on a single H100 node), coupled with its multilingual support and availability on major cloud platforms, will significantly improve its competitiveness for enterprise customers in their AI initiatives.
Licensing and other concerns
One potential concern for users is that Mistral is releasing ML2 under the Mistral Research License, which allows use and modification for research and non-commercial purposes only. For commercial use that requires self-implementation, users must obtain a separate Mistral Commercial License from the company.
“Since Mistral AI must have incurred significant data and training costs for Large 2, they have rightly narrowed the scope of unlicensed commercial use, which requires a strict commercial license, which increases the price and could be an inhibitor,” Shah said. “This can be a deal breaker in certain areas like emerging markets.” Prabhu Ram, vice president of Cybermedia Research’s industry research group, added that while Mistral AI has shown promise and potential, certain concerns remain. These include data transparency, model interpretability, and risk of bias, which remain critical areas for improvement.
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