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There are the following limitations when using Mistral Large via watosonx.ai.
Mistral Large model limit: 128K watsonx.ai limit: 32K
Currently, in the Japanese market, Mistral Large has good accuracy for Japanese, and this model is often used for RAG applications.
If you implement a RAG application with a 32K limit, you will have to reduce the number of documents included in the context by 1/4, making it difficult to maintain RAG accuracy.
This is not a problem for sample applications, but if you are trying to implement a RAG application or AI agent used in production, a context size of 128K is desirable.
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Love it!
If the HW resources can be secured, I would love to see https://huggingface.co/mistralai/Mistral-Large-Instruct-2411 deployed in the Japan region as well.
The Mistral Large model has good Japanese language support and is widely used in the Japanese market.