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Mistral 3 family of models released

mistral.ai

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Re: Mistral 3 family of models released

#151

Post by mrtksn »

giancarlostoro wrote: post #141
mrtksn wrote: post #69

Earlier quoted context omitted.

Some time ago I canceled all my paid subscriptions to chatbots because they are interchangeable so I just rotate between Grok, ChatGPT, Gemini, Deepseek and Mistral. On the API side of things my experience is that the model behaving as expected is the greatest feature. There I also switched to Openrouter instead of paying directly so I can use whatever model fits best. The recent buzz about ad-based chatbot services…

Maybe give Perplexity a shot? It has Grok, ChatGPT, Gemini, Kimi K2, I dont think it has Mistral unfortunately.

I like perplexity actually but haven’t been using it since some time. Maybe I should give it a go :)

Re: Mistral 3 family of models released

#153

Post by JumpCrisscross »

didibus wrote: post #68
apexalpha wrote: post #59

Earlier quoted context omitted.

1. Big problem 2. ASML was propped up by ASM and Philips, stepping in as "VCs"

For VC don't you need a lot of capital and people with too much money? Isn't that then a chicken and egg?

> and people with too much money?

No. VC’s historical capital has come from institutional investors. Pensions. Endowments. Foundations.

Re: Mistral 3 family of models released

#154

Post by cycomanic »

gishh wrote: post #65
Glemkloksdjf wrote: post #31

Earlier quoted context omitted.

Thats not the point. Deepmind is not an UK company, its google aka US. Mistral is a real EU based company.

Using US VC dollars. Where their desks are isn’t really important.

That's such a silly argument. X, OpenAI and others have large Saudi investments. In the grant scheme of things the US is largely indebted to China and Japan.

Re: Mistral 3 family of models released

#155

Post by adam_patarino »

bildung wrote: post #74
constantcrying wrote: post #6

Earlier quoted context omitted.

The lack of the comparison (which absolutely was done), tells you exactly what you need to know.

I think people from the US often aren't aware how many companies from the EU simply won't risk losing their data to the providers you have in mind, OpenAI, Anthropic and Google. They simply are no option at all. The company I work for for example, a mid-sized tech business, currently investigates their local hosting options for LLMs. So Mistral certainly will be an option, among the Qwen familiy and Deepseek. Mistral…

We're seeing the same thing for many companies, even in the US. Exposing your entire codebase to an unreliable third party is not exactly SOC / ISO compliant. This is one of the core things that motivated us to develop cortex.build so we could put the model on the developer's machine and completely isolate the code without complicated model deployments and maintenance.

Re: Mistral 3 family of models released

#156

Post by LunaSea »

DarmokJalad1701 wrote: post #104
LunaSea wrote: post #83

Earlier quoted context omitted.

Upvoting Windows 11 as the US's best effort at Operating Systems development.

Wouldn't that be macOS? Or BSD? Or Unix? CentOS?

What's the market share of those compared to Windows and Linux?

Re: Mistral 3 family of models released

#158

Post by nikcub »

ThrowawayTestr wrote: post #130
trvz wrote: post #89

Sad to see they've apparently fully given up on releasing their models via torrent magnet URLs shared on Twitter; those will stay around long after Hugging Face is dead.

How does HF manage to serve such big files?

s3 + cloudfront

https://huggingface.co/blog/rearchitecting-uploads-and-downl...

Re: Mistral 3 family of models released

#159

Post by acuozzo »

barrell wrote: post #144
acuozzo wrote: post #136

Earlier quoted context omitted.

I have a need to remove loose "signature" lines from the last 10% of a tremendous e-mail dataset. Based on your experience, how do you think mistral-3-medium-0525 would do?

What's your acceptable error rate? Honestly ministral would probably be sufficient if you can tolerate a small failure rate. I feel like medium would be overkill. But I'm no expert. I can't say I've used mistral much outside of my own domain.

I'd prefer for the error rate to be as close to 0% as possible under the strict requirement of having to use a local model. I have access to nodes with 8xH200, but I'd prefer to not tie those up with this task. I'd, instead, prefer to use a model I can run on an M2 Ultra.

Re: Mistral 3 family of models released

#160

Post by pembrook »

mbowcut2 wrote: post #125
barrell wrote: post #38

I use large language models in http://phrasing.app to format data I can retrieve in a consistent skimmable manner. I switched to mistral-3-medium-0525 a few months back after struggling to get gpt-5 to stop producing gibberish. It's been insanely fast, cheap, reliable, and follows formatting instructions to the letter. I was (and still am) super super impressed. Even if it does not hold up in benchmarks, it still out…

It makes me wonder about the gaps in evaluating LLMs by benchmarks. There almost certainly is overfitting happening which could degrade other use cases. "In practice" evaluation is what inspired the Chatbot Arena right? But then people realized that Chatbot arena over-prioritizes formatting, and maybe sycophancy(?). Makes you wonder what the best evaluation would be. We probably need lots more task-specific models. T…

If the models from the big US labs are being overfit to benchmarks, than we also need to account for HN commenters overfitting positive evaluations to Chinese or European models based on their political biases (US big tech = default bad, anything European = default good).

Also, we should be aware of people cynically playing into that bias to try to advertise their app, like OP who has managed to spam a link in the first line of a top comment on this popular front page article by telling the audience exactly what they want to hear ;)

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