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Mistral Large

mistral.ai

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Re: Mistral Large

#241

Post by binarymax »

whazor wrote: post #240
binarymax wrote: post #151

On Azure, it's slightly cheaper than GPT-4. Per 1000 tokens: GPT-4 input: $0.01 Mistral input: $0.008 GPT-4 output: $0.03 Mistral output: $0.024

But there is also GPT-4 turbo

Hey thanks for pointing this out. The prices above are for GPT-4-Turbo and I should have specified. GPT-4 is considerably more expensive.

    GPT-4 (classic, 8k)  input:  $0.03
    GPT-4 (classic, 8k)  output: $0.06

    GPT-4 (classic, 32k) input:  $0.03
    GPT-4 (classic, 32k) output: $0.12
https://azure.microsoft.com/en-us/pricing/details/cognitive-...

Re: Mistral Large

#242

Post by boarush »

whazor wrote: post #240
binarymax wrote: post #151

On Azure, it's slightly cheaper than GPT-4. Per 1000 tokens: GPT-4 input: $0.01 Mistral input: $0.008 GPT-4 output: $0.03 Mistral output: $0.024

But there is also GPT-4 turbo

People have generally resorted to referring GPT-4 Turbo as GPT-4 since it has been in preview for ~4 months and can mostly be used for production loads.

GPT-4 Turbo is priced $10/M Input Tokens and $30/M Output Tokens.

Re: Mistral Large

#243

Post by schrijver »

sekai wrote: post #156
loudmax wrote: post #44

Earlier quoted context omitted.

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".

> I presume most young Francophones who are likely to actually use Mistral will pronounce it in Franglais as "le tchatte" Anything's better than hearing how french pronounce ChatGPT: "tchat j'ai pété" (literally means "cat, I farted" in french).

Uhm, no ? Chat as in cat is pronounced sja. Or sjaht for a female cat (chatte). The tsjaht pronounciation is when using the english word chat in french.

Re: Mistral Large

#244

Post by jug »

speedgoose wrote: post #136
onlyrealcuzzo wrote: post #119

Earlier quoted context omitted.

They compare to Gemini Pro 1.0... Seems intentionally misleading.

Right. Gemini Pro 1.5 scores 81.9% on MMLU and is also above in a few other benchmarks.

With 128K context (1M paid) compared to 32K. Man, Google is going to be a game changer for especially free AI tiers.

Edit: BTW, more Mistral benchmarks here: https://docs.mistral.ai/platform/endpoints/ TIL Mistral Small outperforms Mixtral 8x7B.

Re: Mistral Large

#245

Post by aatd86 »

ot wrote: post #68
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

"Big Mac's a Big Mac, but they call it Le Big Mac"

Only if you know Big Mac personally otherwise it's "Un Big Mac" :oD

Re: Mistral Large

#246

Post by kergonath »

arnaudsm wrote: post #80
WiSaGaN wrote: post #66

Changelog is also updated: [1] Feb. 26, 2024 API endpoints: We renamed 3 API endpoints and added 2 model endpoints. open-mistral-7b (aka mistral-tiny-2312): renamed from mistral-tiny. The endpoint mistral-tiny will be deprecated in three months. open-mixtral-8x7B (aka mistral-small-2312): renamed from mistral-small. The endpoint mistral-small will be deprecated in three months. mistral-small-latest (aka mistral-small…

I know marketing folks prefer poetic names, but I wish we had consistent naming like v1.0, 2.0 etc, instead of renaming your product line every year like Apple and Xbox does. Confusing and opaque.

> renaming your product line every year like Apple and Xbox does.

Apple is famous for not updating product names. This year’s MacBook Pro is just “MacBook Pro”, same as last year’s, and so on since the beginning. You have to dig to get actual names like “M3, nov 2023” or the less ambiguous Mac15,3.

That said, I agree with you. Navigating the jungle of LLMs all over the place with utterly stupid naming schemes is not easy.

Re: Mistral Large

#247

Post by OkGoDoIt »

r00fus wrote: post #162
arnaudsm wrote: post #80

Earlier quoted context omitted.

I know marketing folks prefer poetic names, but I wish we had consistent naming like v1.0, 2.0 etc, instead of renaming your product line every year like Apple and Xbox does. Confusing and opaque.

Apple does it properly - version + moniker. Searching google/etc for specific issues related to version numbers alone is a disaster, so monikers have a use.

Really? Other than the iPhone and Apple Watch which do have clear series naming, I find it basically impossible to determine if any particular Apple product name is the latest version or several years old. The iPads especially, and the MacBooks were pretty confusing until recently. The Apple TV and AirPods are also a bit of a mess. I wish they would just do for all of their products what they do for the iPhone, it would make things so much simpler. But even then, the iPhones are not clearly labeled on the products themselves. If someone hands you a random iPhone, it’s impossible to tell what model is unless you have encyclopedic knowledge of the exact differences between all the different iPhones, or you have the unlock passcode and can get into the settings>about menu.

Re: Mistral Large

#248

Post by mewpmewp2 »

vy007vikas wrote: post #154
cyrusradfar wrote: post #137

Earlier quoted context omitted.

1.5 was probably released too late to be tested.

But Ultra 1.0 is available to compare against, right?

How can I get access to it? The best I can compare against is pro 1.0.

Most of my usecases are logic based on embedded content in the prompt and nothing available to me beats GPT-4 there.

Re: Mistral Large

#249

Post by mewpmewp2 »

renewiltord wrote: post #171
jensensbutton wrote: post #144

Earlier quoted context omitted.

Yes

How do I use it? I only have access to 1.0 Ultra through Gemini Advanced.

And that doesn't count. Only pro 1.0 available for me through APIs. I need to be able to test for myself the capabilities.

As it stands best LLM available by API by Google is far behind GPT4.

Re: Mistral Large

#250

Post by observationist »

tmpz22 wrote: post #186
observationist wrote: post #181

Earlier quoted context omitted.

You shouldn't have had any trust to begin with; I don't know why we are so quick to hold up humans as bastions of truth and integrity. This is stereotypical Gell-Mann amnesia - you have to validate information, for yourself, within your own model of the world. You need the tools to be able to verify information that's important to you, whether it's research or knowing which experts or sources are likely to be trustwo…

> This is stereotypical Gell-Mann amnesia - you have to validate information, for yourself, within your own model of the world. You need the tools to be able to verify information that's important to you, whether it's research or knowing which experts or sources are likely to be trustworthy. Except anthropologically speaking we still live in trust-based society. We trust water to be available. We trust the grocery st…

Oh, for sure - I'm not saying don't do anything about it. I'm just saying you should have been treating all information online like this anyway.

The lesson from Gell-Mann is that you should bring the same level of skepticism to bear on any source of information that you would on an article where you have expertise and can identify bad information, sloppy thinking, or other significant problems you're particularly qualified to spot.

The mistake was ever not using "Trust but verify" as the default mode. AI is just scaling the problem up, but then again, millions of bots online and troll farms aren't exactly new, either.

So yes, don't let AI off the hook, but also, if AI is used to good purposes, with repeatable positive results, then don't dismiss something merely because AI is being used. AI being involved in the pipeline isn't a good proxy for quality or authenticity, and AI is only going to get better than it is now.

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