The featured accuracy benchmarks exclude every model that matter except DeepSeek, which is quite telling about this new model's performance.
This makes it yet another example of European companies building great products but fumbling marketing.
Mistral's edge is speed. It's a real pleasure to use because it answers in ~1s what takes other models 5-8s, which makes for a much better experience. But instead of focusing on it, they bury it far down the post.
Try it and see if you like the speed! Note that the speed advantage only applies to queries that don't require web-search, as Mistral is significantly slower on this one, leading to a ~5 seconds advantage over 2 minutes of research for the queries I benchmarked with Grok.
How would you use a fast AI?
My current use of AI is to generate code - or translate some code from a programming language to another - which I can then improve (instead of writing it from stratch). Speed isn't necessary for this. It's a nice-to-have but only if it's not at the cost of quality.
Also, as unfair as it "might" be, we do expect a fast AI not to be as good, don't we? So I wouldn't focus on that in the marketing. I think speed would be easier to sell as something extra you would pay for, because then you'd expect the quality to remain the same or better.
That is reasonable though. Comparing the product of a small company with little resources with giants like Google and OpenAI in a field where most advances are due to more and more expensive models is nonsense.
The point I was trying to express is that Mistral is arguably far superior to the giants if you care about speed! So I wished they communicated this more clearly.
I tried thinking with websearch on their website.
It has similar speed with o4-mini with search on chatgpt, and o4-mini gave me much better result.