Is the number of em-dashes in this marketing copy indicative of the kind of output that the model produces? If so, might want to tone it down a bit.
Unless you're a lawyer. We love 'em.
Magistral — the first reasoning model by Mistral AI
41–50 of 444 posts
Re: Magistral — the first reasoning model by Mistral AI
#42Re: Magistral — the first reasoning model by Mistral AI
#43Re: Magistral — the first reasoning model by Mistral AI
#44Earlier quoted context omitted.
"EU is leading in regulation", they say. I don't know what they are thinking.
probably some silly thing like "people should have more rights and protections"
EU regulation is often "you can not have the cool thing" not "the cool thing must be operated equitably".
I think they are more interested in protecting old money than in protecting people.
Re: Magistral — the first reasoning model by Mistral AI
#45Re: Magistral — the first reasoning model by Mistral AI
#46Earlier quoted context omitted.
Europe isn't going to catch up in tech as long as its market is open to US tech giants. Tech doesn't have marginal costs, so you want to have one of it in one place and sell it everywhere and when the infra and talent is already in US, EU tech is destined to do niche products. UK has a bit of it, France has some and that's it. The only viable alternatives are countries who have issues with US and that is China and Ru…
If you close off the market to US tech giants, maybe they'll have some amount of market dominance at home, but I would doubt that would mean they've "caught up" tech wise. There would be no incentive to compete. American EV manufacturing is pretty far behind Chinese EV manufacturing, protectionism didn't help make a competitive car, it just protected the home market while slowly ceding international market after inte…
As a counterexample, China's tech industry has caught up and in some ways surpassed the US, partially due to being closed off.
Re: Magistral — the first reasoning model by Mistral AI
#47Earlier quoted context omitted.
"EU is leading in regulation", they say. I don't know what they are thinking.
Sorry, this is just getting old... Its a trite talking point and not the reason why there are so few consumer-AI companies in Europe.
And what would be the reason? I am genuinely interested. Also, are there viable not "consumer" AI companies here? Only Mistral seems to train foundation models, and good for them, however, as of now they are absolutely not SOTA.
Re: Magistral — the first reasoning model by Mistral AI
#48Benchmarks suggest this model loses to Deepseek-R1 in every one-shot comparison. Considering they were likely not even pitting it against the newer R1 version (no mention of that in the article) and at more than double the cost, this looks like the best AI company in the EU is struggling to keep up with the state-of-the-art.
> Benchmarks suggest this model loses to Deepseek-R1 in every one-shot comparison.
That's not particularly surprising though as the Medium variant is likely close to ten times smaller than DeepSeek-R1 (granted it's a dense model and not an MoE, but still).
Re: Magistral — the first reasoning model by Mistral AI
#49Earlier quoted context omitted.
probably some silly thing like "people should have more rights and protections"
EU regulation is often "you can not have the cool thing" not "the cool thing must be operated equitably". I think they are more interested in protecting old money than in protecting people.
Can you name specific examples? Otherwise, this just sounds like inflammatory polemic.
Re: Magistral — the first reasoning model by Mistral AI
#50I made some GGUFs for those interested in running them at https://huggingface.co/unsloth/Magistral-Small-2506-GGUF ollama run hf.co/unsloth/Magistral-Small-2506-GGUF:UD-Q4_K_XL or ./llama.cpp/llama-cli -hf unsloth/Magistral-Small-2506-GGUF:UD-Q4_K_XL --jinja --temp 0.7 --top-k -1 --top-p 0.95 -ngl 99 Please use --jinja for llama.cpp and use temperature = 0.7, top-p 0.95! Also best to increase Ollama's context length…
But this is just the SFT - "distilled" model, not the one optimized with RL, right?
Oh I think it's SFT + RL as mentioned in the paper - they said combining both is actually more performant than just RL