I wish for this company to have great models. I am glad to see such good scores.
I see they have a HuggingFace account[0] and they fine-tuned GPT-OSS, Nemotron, and Qwen, in the past under new names.
There are some things about it that make me worry though.
• They don't indicate the active parameter count, or indicate whether they pretrained the model. It could be a MiniMax M3 finetuning, as the parameter count almost matches (435B vs. 438B).
It would not be the first company with a splashy release, like Brampton Intelligence[1], or SubQ[2].
Unlike those, they do seem to have experience fine-tuning models. Regardless of my worries, I am rooting for them to learn how to train models.
I do not want open weight models from China to be the only viable locally hosted things (deepseek v4 flash 0731 Q8, qwen 3.8-flash-next Q8, GLM-5.3-Flash) in the under 200GB RAM class.
I want to see things like Mistral and Laguna (non-CN) succeed. I have spent about a week using Laguna S 2.1 as a test and while I wasn't blown away by its capabilities, it's also totally acceptable for many purposes.
I do hope these Quasar people learn that if you announce a new model and it already performs worse than things people can go download from huggingface, and/or buy access to with very cheap token plans via openrouter or opencode.. If your new model is API only and people can't download/examine it, it will get very little uptake and real world use.
I can see it as a niche market for european sovereignty stuff if absolutely necessary, hosted and run in Europe, sure. Same as Mistral. That's a niche which exists, there's probably enough room for a couple of modestly sized companies doing it... I guess?
I understood from informal chatter that researchers in the top Chinese labs are pretty open with sharing knowledge with each other. Additionally, it seems that anywhere between 30-50% of key researchers in the top US labs are ethnically Chinese. I wonder if this situation might give Chinese labs/researches some advantage just due to language and informal networks. Chinese researchers can understand all the English research, but research in Chinese is far less accessible to non-Chinese.
It's not a small niche. Anything touching European resident personal data must only be done by Euro AI Act compliant AIs. So, hosted in Europe at least (unclear to me rn, would love to learn the exact criteria).
But is it compliant if someone runs, for example, self-hosted GLM5.3 on euro owned and administered hardware that's located in Europe? That would remove a lot of the incentive for there to be EU labs building models.
Didn't know the "Highest scoring EU model" has a low bar, lower than Qwen3.8-27B, but still congratulations on the milestone, hopefully next iterations will get better from here
It is surprising given how many parameters it has that it scores so low. But, hopefully this will build up domestic talent and understanding and let Europe compete on the world stage with this.
3.8-flash-next quantized in a "large" Q4 that just fits in 128GB RAM even more so, in how close it can get to state of the art in a number of benchmarks. Or a large Q8 version of it that fits in under 190GB. Competing against things that are closed weights/opaque information about the model and might very well be 600B+ in size.
I hope you're aware that it's likley in the future open weight models will output tokens/commands that aren't in your interest. It could be that models are trained with spionage in mind and models could only target specific input token patterns, time zones, ip addresses, names etc... You will be able to see the output tokens but things will become so complex that you won't notice its intentions. Maybe there will be some sort of output token scanning software/llm (let's call it a modern form of a virus scanner) that validates intentions. In the end, I'm just trying to say that open weight means you have a black box in front of you that you don't know what it does. Therefore, the training material of open weight models should be known. While it doesn't matter where the model comes from, it certainly matters whether you trust those people if you don't have the training material.
> the state that has to buy all its water and food from its aggressive, militarized neighbour.
As a complete tangent, now imagine being a Canadian and realizing how much of your fresh fruits and vegetables come from the USA (or if from Mexico, through the USA).
The problem is always the next model, or the one after. If china thinks it's beneficial to stop open weight releases, it will stop them. Then you are stranded on that one and no local industry to produce new models for you.
That's a very limiting view of things. A model, even an open weight one, is never neutral, it is an encoding of a way of viewing the world.
What kind of "alignment" are AI labs optimizing for? Ideological alignment is the full term, self-censored into something more technological-sounding.
Every model has people behind it rating what it should and shouldn't say. Every time you ask a model and trust its answer, you become ever-so-slightly ideologically indoctrinated.
I don't want my model to reflect the views of American oligarchs or Chinese cadres. I want European values of enlightenment and humanitarianism to be the default.
>I don't want my model to reflect the views of American oligarchs or Chinese cadres. I want European values of enlightenment and humanitarianism to be the default.
I don't want AI models to reflect any kind of values whatsoever. I have my own views - thank you - and I don't need other throwing their values in my face using AI.
I prefer AI models not being trained ideologically.
There is no unideological. There is no view from nowhere, what you perceive as unideological is precisely the reflection of your own ideology. The "unbiased" is just whatever matches your own bias.
To quote Zizek:
> I already am eating from the trashcan all the time. The name of this trashcan is ideology. The material force of ideology - makes me not see what I'm effectively eating. It's not only our reality which enslaves us. The tragedy of our predicament - when we are within ideology, is that - when we think that we escape it into our dreams - at that point we are within ideology.
What I want is a model that is trained with data that is openly available, where the data is curated by academia. I don't want corporate crap in my AI (unless it has been filtered properly).
I'm ready to stand corrected, but I'm pretty positive that such a process would require 1) an insane amount of work and 2) wouldn't produce anything close to SOTA results because of the lack of training data.
It is my understanding that - sadly - the insane amount of copyrighted works and corporate crap is a prerequisite for having a corpus that is big enough
I think these days even the frontier labs are using large amounts of synthetic data too, which must be worth it even though it seems like an Ouroborous.
Individual Indians are very much present in companies like OpenAI, Anthropic, etc. I have a theory that the top 5% talent of Indian nationals who are legitimately qualified and skilled, for very logical reasons would much rather take a six-figure USD equivalent salary in EUR or USD and enjoy the lifestyle benefits that come with it rather than bootstrap an Indian domestic AI lab.
I see they have a HuggingFace account[0] and they fine-tuned GPT-OSS, Nemotron, and Qwen, in the past under new names.
There are some things about it that make me worry though.
• They don't indicate the active parameter count, or indicate whether they pretrained the model. It could be a MiniMax M3 finetuning, as the parameter count almost matches (435B vs. 438B).
• They mention using quantum algorithms in other projects: https://multiversecomputing.com/singularity despite quantum algorithms not being typically useful currently.
It would not be the first company with a splashy release, like Brampton Intelligence[1], or SubQ[2]. Unlike those, they do seem to have experience fine-tuning models. Regardless of my worries, I am rooting for them to learn how to train models.
[0]: https://huggingface.co/MultiverseComputingCAI
[1]: https://x.com/newsystems_/status/1904577550690771050
[2]: https://subq.ai/introducing-subq
I want to see things like Mistral and Laguna (non-CN) succeed. I have spent about a week using Laguna S 2.1 as a test and while I wasn't blown away by its capabilities, it's also totally acceptable for many purposes.
I do hope these Quasar people learn that if you announce a new model and it already performs worse than things people can go download from huggingface, and/or buy access to with very cheap token plans via openrouter or opencode.. If your new model is API only and people can't download/examine it, it will get very little uptake and real world use.
I can see it as a niche market for european sovereignty stuff if absolutely necessary, hosted and run in Europe, sure. Same as Mistral. That's a niche which exists, there's probably enough room for a couple of modestly sized companies doing it... I guess?
It's not a small niche. Anything touching European resident personal data must only be done by Euro AI Act compliant AIs. So, hosted in Europe at least (unclear to me rn, would love to learn the exact criteria).
15 tk/s isn't useless if you can give it big tasks to do overnight, or like ask it to do something and check back 3-4 hours later.
As a complete tangent, now imagine being a Canadian and realizing how much of your fresh fruits and vegetables come from the USA (or if from Mexico, through the USA).
E.g. I had random, completely unrelated and irrelevant fetch by Qwen3.8 27B to " https://routify-file-proxy-sg.oss-ap-southeast-1.aliyuncs.co..." and I only noticed it because I have allowlist rules for what they can do.
What kind of "alignment" are AI labs optimizing for? Ideological alignment is the full term, self-censored into something more technological-sounding.
Every model has people behind it rating what it should and shouldn't say. Every time you ask a model and trust its answer, you become ever-so-slightly ideologically indoctrinated.
I don't want my model to reflect the views of American oligarchs or Chinese cadres. I want European values of enlightenment and humanitarianism to be the default.
I don't want AI models to reflect any kind of values whatsoever. I have my own views - thank you - and I don't need other throwing their values in my face using AI.
I prefer AI models not being trained ideologically.
To quote Zizek:
> I already am eating from the trashcan all the time. The name of this trashcan is ideology. The material force of ideology - makes me not see what I'm effectively eating. It's not only our reality which enslaves us. The tragedy of our predicament - when we are within ideology, is that - when we think that we escape it into our dreams - at that point we are within ideology.
It is my understanding that - sadly - the insane amount of copyrighted works and corporate crap is a prerequisite for having a corpus that is big enough