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Mistral Large

mistral.ai

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41–50 of 282 posts

Re: Mistral Large

#41

Post by jsnell »

hobofan wrote: post #18
Larok00 wrote: post #3

There is not a lot of advantage to releasing this on Azure where you are directly competing with GPT-4, which will beat you on most tasks.

I would assume that the advantage (for Mistal) here is Microsoft paying them money to be the exclusive model hosting partner, so that everyone has to go to Azure to get top-tier hosted models.

It's obviously not exclusive (it's available hosted from both Mistral themselves and Azure). I guess it could possibly be exclusive within some smaller scope, but nothing in the article suggests that. Azure is described as the "first distribution partner", not an exclusive one.

Re: Mistral Large

#42

Post by polycaster »

thomastay wrote: post #40
polycaster wrote: post #37

Pricing doesn't seem to be a topic of interest on Mistral's public pages. I feel I'm missing the point somehow, because "what does it cost" was my first question.

It's $8/24 per M input/output tokens. For reference, GPT4-Turbo is 10/30, and GPT4 is 30/60 https://docs.mistral.ai/platform/pricing/

Thanks!

Re: Mistral Large

#43

Post by rafram »

tomkaos wrote: post #16
Larok00 wrote: post #3

There is not a lot of advantage to releasing this on Azure where you are directly competing with GPT-4, which will beat you on most tasks.

You probably get a better control on what a happen with the data. I have the impression that GTP-4 is more of a black box and privacy problem.

GPT-4 on Azure has the exact same privacy situation as Mistral on Azure. Microsoft hosts the models on its own servers.

Re: Mistral Large

#44

Post by loudmax »

syntaxing wrote: post #14

Interesting, I didn’t know they had le chat. I’ve been wanting a chatgpt competitor with mistral. Also love the fact they put “le” in front of their products

Cute, but "le chat" literally means "the cat".

I presume most young Francophones who are likely to actually use Mistral will pronounce it in Franglais as "le tchatte".

Re: Mistral Large

#45

Post by thenaturalist »

pama wrote: post #4

It is very nice to see the possibility of self deployment. Does anyone have experience with self deployment of such a large model in a company setting?

No reference to self-deployable Docker images for large as of now.

Only 7B and mixtrail exist.

https://docs.mistral.ai/self-deployment/vllm/

Re: Mistral Large

#47

Post by michaelt »

pradn wrote: post #11
rntc wrote: post #2

Looks like open-source is just a marketing tool for AI companies before they have a good enough model to sell. I guess we have to look for what Meta is going to do with LlaMA 3.

How is this a problem? So many companies have been founded around premium versions of open-source products. It's good that they've even given us as much as they have. They have to make the economics work somehow.

It's not a problem from a moral perspective or anything - we all know these models are very expensive to create.

However, from a marketing perspective - think of who the users of an open model are. They're people who, for one reason or another, don't want to use OpenAI's APIs.

When selling a hosted API to a group predominantly comprised of people who reject hosted APIs - you've got to expect some push back.

Re: Mistral Large

#48

Post by gpayan »

rntc wrote: post #2

Looks like open-source is just a marketing tool for AI companies before they have a good enough model to sell. I guess we have to look for what Meta is going to do with LlaMA 3.

The cash required to develop and train the models makes the open-source approach challenging, if not impossible, for companies who don't have another business to support it. You need to be Meta - with a huge cash cow - to have the option to give away your work for free. After all OpenAI tried and came to the conclusion that it couldn't succeed as a pure open-source non-profit company no?

Re: Mistral Large

#50

Post by zozbot234 »

HPsquared wrote: post #12
rntc wrote: post #2

Looks like open-source is just a marketing tool for AI companies before they have a good enough model to sell. I guess we have to look for what Meta is going to do with LlaMA 3.

Especially as the model weights are literally a huge opaque binary blob. Much more opaque than even assembly code. There is plenty of precedent for what "open source" means, and these aren't it. Edit: not that I mind all that much what they're actually doing, it's just the misuse of the word that bristles.

Open source means "the preferred version for modification" and this fits with model weights since you can fine tune them with your own data. Modifying raw training data would be quite unwieldly and pointless.
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