Charlie Dai, VP and principal analyst at Forrester, also noted that Mistral LLM-2’s advanced features in code generation, mathematics, reasoning, performance, and cost efficiency — designed to run efficiently on a single H100 node — along with its multilingual support and availability on major cloud platforms, will significantly enhance its competitiveness for enterprise clients in their AI initiatives.
Licensing and other concerns
A potential concern for users is that Mistral is releasing ML2 under the Mistral Research License, allowing usage and modification only for research and non-commercial purposes. For commercial use that requires self-deployment, 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 reduced the scope for commercial usage without a license, requiring a strict commercial license, which drives up the pricing and could be an inhibitor,” Shah said. “This may be a deal breaker in certain areas like emerging markets.” Prabhu Ram, VP of Industry Research Group at Cybermedia Research, added that while Mistral AI has shown promise and potential, certain concerns persist. These include data transparency, model interpretability, and the risk of bias, which remain critical areas for improvement.
