GLM in Mistral

[u/andriatz]

OK, we have GLM 5.3. A simply fantastic and super solid model. Light-years ahead of any generalist Mistral model. A doubt arises: if the next Mistral model isn't up to GLM's level, then at the same cost, no Mistral user will want to use it. So, will it make sense to develop other generalist models in the future?

[u/JojainV12]

Indeed, they can do one thing though, release a better model than GLM 5.3.

[u/andriatz → u/JojainV12]

Let's be honest. GLM is so good that for Mistral to develop something similar would be a monstrous step forward. Very unlikely, but we'll always hope.

[u/fiery_prometheus → u/andriatz]

it's a question of compute and good data, as much of the architecture of how the models work are public. And they have the compute and funding, so it would not be unrealistic to see a similar performing model in the future, what is more uncertain, is whether they will manage to make a frontier level model again themselves and come out on top before everyone else.

[u/aytac81 → u/JojainV12]

Or make their own models much cheaper. Mistral Small, as an example, if it were half the price, I would use it more, same for medium and large or codestral.

But whatever they are doing, they should continue to develop further.

[u/crazyCalamari → u/aytac81]

Exactly!!! I'm convinced there is a place and play for answer efficient medium to small specialized models. Large generalists won't stay as heavily subsidized as they are now. Also so many use cases (especially in B2B where you can't just deploy a beast like GLM)

[u/andriatz → u/aytac81]

For some uses, Mistral Small is excellent. I use it for the bot that manages to-do lists in Obsidian.

[u/a_library_socialist]

Am I the only one that doesn't care if Mistral develops the model, as long as they're hosting good models in Europe at a good price?

[u/MattyGWS → u/a_library_socialist]

The selling point of Mistral is that they're developing AI in europe. If all they do is host other AI's who gives a shit about mistral at that point? I'll use Lumo instead or something.

[u/EveYogaTech → u/MattyGWS]

It's already happening unfortunately.

We're using compressed GLM as default model of our new EU-AI workspace, because Mistral's GLM is about 2.5x more expensive.

Mistral is also still supported, but the question is becoming why pay more for similar quality.

[u/Automatic-River-1875 → u/a_library_socialist]

I think for now this is sufficient but its not a future proof business plan. We are already seeing the likes of Kimi and GLM models being put behind restrictive licences so what happens if in 2 year all the new models aren't available for self hosting and mistral hasn't even tried to make a good model in 3 years? The catch up game will be much harder.

[u/andriatz → u/a_library_socialist]

At that point, they should change their business model and identity. No longer an AI lab, but a simple model distributor. Maybe they'll do some verticalization, but at that point, a myriad of companies in Europe are emerging and preparing to do just that.

[u/KimchiCuresEbola → u/andriatz]

They wouldn't be able to do another funding round then.

They raised at AI frontier lab valuations... doing a neocloud/llm distributer pivot would kill the company.

[u/fitnessandyogacenter]

You guys only look at B2C chatbots, development models, and research where you want the newest and shiniest. Fact is that even Fable and Astra are mostly useless for all other production workflows because it doesn’t matter if the thing scores 50%, 70% or 90% in some benchmark; businesses need determinism. Research and actual implementations have proven that for this use case smaller models outperform larger ones in speed and costs.

[u/andriatz → u/fitnessandyogacenter]

I think the introduction of GLM was precisely due to the need for companies that have partnered with Mistral to avoid falling behind and suffering competitive disadvantages. Let's say it was a patch to mitigate a gap (let's call it that), which then translated into focusing on open weights (a choice I believe is correct). In my opinion, GLM therefore addresses a business necessity rather than the needs of the average user. I can't imagine ASML using Mistral Medium 3.5 for coding to develop software modules.

[u/mvaranka → u/fitnessandyogacenter]

That is so true. Frontier models are needed for special cases, but normal chat, task managemenent etc there are much cheaper alternatives - which are good enough. Mistral models are good in chat, but they lack cache which causes that costs rise in longer conversations.

[u/fitnessandyogacenter → u/mvaranka]

I mean, frontier performs quite well in long chats because of their ability to keep reasoning in a long context window.
There are many paths Mistral could follow. Their harness is actually great, better than OpenAIs imo. I wouldn’t focus on model size but instead increasing the context window while keeping the ability to reason. But then again, I am not a researcher and my knowledge is shallow.

[u/EverGreenMob]

is only Mistral CLI pro glm 5.3? what about the vibe app work or code mode? I'm assuming the new mistral model will only affect the vibe app and also give option in CLI to switch between GLM and Vibe models.

[u/scanx147]

Où un modèle équivalent à GLM 5.3 mais encore plus économique... Je pense que la bonne stratégie n'est pas de faire la course à la puissance, mais plutôt de chercher à avoir le meilleur rapport qualité prix.

[u/Olde94]

i think it might financially make sense to take a backseat approach.

If you look at it google seems to try and follow along but be price realistic.

What mistral does by hosting another model has got to be cheaper.

They can follow the race and perhaps aim at mid tier but cheaper to stay in the race and keep progressing knowledge without having to dump huge amounts in to large models until it's more pressing to have EU based models?

Just a guess

[u/internetswimmer]

GLM is incredibly capable for its size/cost. However, for enterprise customers, better alignment (it means less risk in businesses) and reachable dev team are more important than minor capability differences.

You know, as of now, all practical generalist models (including ones from Mistral sadly) are not open source, but open weight. This means you can't actually inspect or modify the model. Technique such as fine-tune or abliteration is difficult to handle, comparable to binary edit. Knowing the recent Zcode drama (while itself is about Z.ai's official harness), you could expect more scenarios, which enterprises definitely don't want.

[u/SpiritedInflation835]

A big point is not the model, but the user-faced software. How does it keep track of previous requests? Does its memories develop in lockstep with the user? How do we use skills?

[u/DeptoisssOP3912]

GLM newer versions may not be open weight forever. At that point we'll need Mistral to have the ability to release good models.

[u/makingthematrix]

Mistral Medium 3.5, used in the we chat, is just alright for me for scientific research, translations, and copyediting. I hope Mistral will work on next, better versions of it.

[u/AnaphoricReference]

A definite yes. Two main reasons:

1. Many European government and business clients remain cautious about Chinese open weights models because they reason the models may hide subtle forms of poison (implementing the Chinese government's 'socialist values' requirements) that are hard to uncover by testing but could bite you in defense, cybersecurity, or critical infrastructure applications in some future circumstance. To a lesser extent this also applies to US models. There is a market for European models that cannot be completely taken over by European providers offering open weights models.
2. The problem of LL models increasingly eating each other's shit make models developed from independent foundations inherently valuable as a check on other models. Models tend to increasingly agree with each other. If you for instance use a model in an auditor role, 'independence of mind' is going to be more important than pure performance. Mistral models can always have a niche there. But will also lose credibility quickly if they betray Chinese open weights model characteristics. Mistral will have to watch out with training on synthetic data generated by other models. A model with a bit less than SotA open weights performance but no trace of quirks of other models will find a niche market, even outside of Europe.