I’m using it, all I know is it’s called “Le Chat”, is that what’s meant by model? - as you can tell I’m not very technical.
I use it for generic simple queries. No idea how it compares with the others as I’ve not used them. I’m using it, as the title suggests "they’re not American*
I see. Mistral was the favorite in self-hosted LLM circles back in 2023-2024 but general opinion is that they have since been far surpassed by Chinese and American models, hence my question.
Good to know they’ve found a market with their online offering.
I was a paying customer of Mistral for about a year, it’s quiet good… but nevertheless I moved to Google this month. Gemini is - at least in my experience - simply oh so much better…
Depends on what you are looking for. Mistral’s strong suite is that it can use most, if not all European languages. Also Mistral’s basic architecture is much more (cost & energy) effective due to the use of their use of seperate expert nodes iirc.
Is there a use case where Mistral still beat Qwen or Gemma? If you’re using Mistral, which model and what do you use it for?
qwen suck in Danish. Much better with Mistral.
I’m using it, all I know is it’s called “Le Chat”, is that what’s meant by model? - as you can tell I’m not very technical.
I use it for generic simple queries. No idea how it compares with the others as I’ve not used them. I’m using it, as the title suggests "they’re not American*
I see. Mistral was the favorite in self-hosted LLM circles back in 2023-2024 but general opinion is that they have since been far surpassed by Chinese and American models, hence my question.
Good to know they’ve found a market with their online offering.
I was a paying customer of Mistral for about a year, it’s quiet good… but nevertheless I moved to Google this month. Gemini is - at least in my experience - simply oh so much better…
Depends on what you are looking for. Mistral’s strong suite is that it can use most, if not all European languages. Also Mistral’s basic architecture is much more (cost & energy) effective due to the use of their use of seperate expert nodes iirc.