Notes from the Mistral AI Now Summit in Paris

Notes from the Mistral AI Now Summit in Paris(koenvangilst.nl)

177 points by vnglst 2 hours ago | 39 comments

OK, I'm 100% rooting for both Mistral and task focused small models.

But Mistral has fall really far behind since 2025Q3. It seems they can't get good reasoning models working at even medium context sizes, which is necessary to be at the table right now.

Gemma4 and Qwen3.6 are currently best in the small size; Mistral's "small" model has ~4x the parameter count at 120B and isn't even competing with models a quarter its size.

Back one year ago with Mistral Small 3.1 they were keeping up, but they've fallen into irrelevancy right now.

If Mistral seriously wants to play the on-prem and small task-specific model game, a decent proxy would be to build models that get the r/localLlama crowd excited

greyskull 27 minutes ago | |

> task focused small models

This is tangential: and forgive my ignorance here, but is there an inherent reason why there aren't smaller, focused models from the frontier model providers?

I'm thinking something like a software-specific subset of Opus that is the default for use in Claude Code. Smaller, cheaper to deploy and consume, maybe faster.

pavpanchekha 10 minutes ago | | |

OpenAI used to make Codex-specific models, but they stopped. What I've gathered from interviews and similar is that training two models isn't worth the (small) lift from having a coding-specific model. You're pre-training on everything anyway, and coding RL is reasonably useful for general-purpose models too.

ar0 17 minutes ago | |

I agree. I am a paying Le Chat Pro user, really rooting for a European alternative. But the quality difference between Mistral and the frontier labs is growing too big to ignore. It’s worrying to me that they didn’t talk much about new models at the conference, because that is really where their focus should be IMHO.

I am wondering what is keeping them back, though: Money? Compute? Skills? Training data? My fear is that you are really only getting really good models by training on very dubious data (outputs from the frontier models etc) and that Mistral is too European and too enterprisey to take those risks.

baq 37 minutes ago | |

agreed, the next price increase from frontier labs (and the inevitable limits decrease in subscription tiers) will have people thinking real hard about their model providers and that's when mistral should be ready. however, given their recent performance, I realistically don't have my hopes high up.

djvdq 22 minutes ago | | |

Also, new Medium 3.5 is far more expensive than previous Mistral models, and much more expensive than e.g. Deepseek

lettergram 1 hour ago | |

We actually found the Mistral Small 4, quantized to 4bit was comparable to Qwen 3.6 27B and is roughly the same size. At least from our experience on our use cases, the quantization of the Mistral model worked far better than trying to quantize the Qwen family.

Fully agree to your point though, Mistral in general is far behind where I'd expect and Qwen in particular is crushing it at the smaller sizes.

Personally, I'd consider anything 20B params and above a "medium" model. Small being <20B and large >100B. I think obviously we can get to the huge 1-2T param models, but frankly the margin of accuracy improvement for the speed hit is kinda insane (1-2% for many metrics).

echelon 1 hour ago | |

Nobody trying to compete with Google, OpenAI, and Anthropic should be playing the small models / local models game.

Foundation model labs should be building very large reasoning models, then leaving it to the community to distill them down.

You can't scale a small model up, but you can scale a small model down.

I'm convinced the only way we'll have a seat at the table in the future and avoid total runaway takeoff is if there are very large models within 80% of the capabilities of the frontier models. Tiny RTX models do diddly squat to remain competitive.

Build open weights models for running on H200s. I'll spin them up on RunPod or Lambda.

farley13 33 minutes ago | | |

I do think there's a chance open weight models have a bit of a moment with the costs of frontier models growing on business balance sheets. It's unfortunate from my "privacy loving" PoV that it's mostly Chinese models filling the gap. ( the top models on openrouter for instance ).

I have used Mistral models out of pure ideology for web agents and the like which aren't doing a lot of heavy lifting.

ahnick 39 minutes ago | | |

I thought distillation meant small models don't have to compete with the big models and can always eventually achieve close parity, but it's just a matter of time to do the distillation? (i.e. how much lag do you want to live with) Am I oversimplifying?

simonw 1 hour ago |

> BNP Paribas runs Mistral models on-prem for KYC in Belgium, with sensitive data staying within the bank's walls. Abanca is using agent orchestration to handle sensitive customer information at a huge scale (2 million customers in their app). For European companies in regulated industries, this is a good alternative to relying on US hyperscalers.

Mistral leaning into on-prem and European-hosted models is very smart.

antirez 39 minutes ago |

I really want Europe to be part of the AI development and research. And I strongly cheered for Mistral. But they are accumulating too much technological delay. This needs to be fixed, otherwise it will turn into yet another proof we are not able to run large tech with good results. Basically any Chinese lab is doing much better. It's not Mistral that created I don't want to say DeepSeek, but MiMo 2.5, Minimax 2.7, and so forth. There are only weaker and/or larger and slower (no MoE) models. Not good.

b65e8bee43c2ed0 26 minutes ago | |

https://en.wikipedia.org/wiki/Artificial_Intelligence_Act#Ri...

Europe shot itself in the dick with this hastily implemented at the height of mass hysteria bullshit and now no sane company will build anything there. an AI startup in the US or China can be a boy and his computer. in Europe, the boy needs a dozen lawyers.

Mistral's sinking into irrelevancy despite the head start they had, the very promising early models they released, and the funding they receive, might very well be the consequence of trying to comply.

djvdq 18 minutes ago | | |

It's yet another time when EU is killing our own possibilities to build real competition to US or Chinese tech.

And yet another time they will be thinking aloud in few year "what happened that we are fully dependent on USA?"

tnolet 28 minutes ago |

Regardless of the business. Their website design is :chefs-kiss https://mistral.ai/

davey48016 13 minutes ago | |

I love everything about Mistral's branding.

Eldodi 1 hour ago |

I was at the event, and was impressed by the attendance, all the leaders from the major european listed companies were there.

Also interesting to note the number of partners they invited. Going from Microsoft, Accenture and EY to startups like alpic.ai or lingo.dev . Seems like they are ramping up their M&A game too

petcat 1 hour ago |

> Abanca is using agent orchestration to handle sensitive customer information at a huge scale (2 million customers in their app).

Maybe my perspective is skewed on what "huge scale" means, but 2 million users? That's like a few hundred megabytes of data? Or a couple GBs if there's a lot of per-user data?

vnglst 1 hour ago | |

Maybe, but using state-of-the-art large language models to solve customer support queries with agentic can quickly use a lot of tokens. What I understood from the talk is that they used agents with limited responsibility and (assumption from me) smaller models, to the make sure the answers were quick, reliable and not too costly.

hadlock 1 hour ago | | |

There are several payments processing companies that are already largely using AI for customer support queries. They still have an escape hatch to a human but at least one of those companies (on the smaller side) is reporting a ~99% success rate, they are down to a handful of human customer service employees now for cases where the customer can't find/produce the transaction ID.

fidotron 1 hour ago | |

European consumer focused businesses do not scale easily the same way US ones do, which is a major contributor to their problems developing tech businesses generally.

OTOH such things can be quite defensible, they just rarely become anything like as profitable.

LucidLynx 2 hours ago |

As an European: 100x YES!

I really like the direction and the transparency of Mistral, among those players.

dtang2718 27 minutes ago | |

Even as a non European, it's great to see some competition from Europe against the US/Chinese models.

ogou 57 minutes ago |

I've said it before that Mistral is underrated. They are looking at real world use of LLMs and tooling. Bespoke models are very appealing to lots of non-tech centered companies and state agencies. Also, Mistral's actual platform is useful. While others are watching performance leaderboards like this is some eSports stream, they are building real world uses.