Nvidia Nemotron is also an open training source model, though a portion of its dataset remains proprietary.
Quoting lambda's comment:
> Note that the Nemotron models are generally stronger than Olmo and K2 Think V2 (according to Artificial Analysis benchmarks), and there is a lot of overlap in their datasets (lots of datasets are based on the same sources with different filtering, Olmo and K2 Think V2 both have used some Nemotron datasets).
> But yeah, Nemotron is a modern and fairly capable LLM, even the 122b is more capable than Deepseek R1 (a 671b model) on most benchmarks, and there's also the recently released 550b Ultra now.
In fact, if the frontier companies had taken their approach, it would have started much slower, but I think we would be far more advanced by 2035. Instead we have a majority of society that wants to see AI fail.
IsaacSim was (and might still be) the best robotic learning sim and I ran MLAgents.
I empathize with this but curious what would make any other country a better safehaven for your data? I personally like the EU's approach to data safeguards, but are there other locales/data protections you have in mind that would keep your data "safe".
Let's say Gemini gets to AGI by tomorrow, will my Google account access, or Gemini apps access and data be blocked if I'm not a US citizen? (Anthropic did it with a 5% better model).
If US is classifying the model access based on citizenship, that's similar to treating it as a Defense capability.
From a practical perspective, I'm not sure any servers are safe anywhere...depending on who may want your data.
Compel you to reveal your secrets, including your passwords by threatening to arrest and detain you without legal proceedings for an unspecified period.
Deny your basic human rights, particularly at the borders, especially if you aren’t a citizen.
And more.
It is a commonly accepted "fact" right now, outside the US, that the US is not to be trusted (right now), due to some orange guy, and his mates, manipulating markets, running their mouths, doing all kinds of criminal and/or infantile shit.
I'd say there is quite a bit of evidence for this all around.
Frankly, I'm surprised there's not more urgency on the part of Europeans to reduce dependence on US tech. I don't like it. I'm an American in tech. But, the US can't be trusted, at this time. And, given how irresponsible tech leadership has been, in kowtowing to Trump, I don't see how they can reasonably be trusted, either.
Stallman was correct in the 80s and is correct now about libre software
My last hope for soverign AI is from Chinese open models
If you want to mix models like this, check out https://github.com/deepbluedynamics/nemesis8
> What most people miss IMO is that this is not a team who is doing this for the fourth time like virtually any other LLM provider and who could learn from its own past experiences. I bet if the team would do another model training they could get way better results at one fourth of the costs.
i doubt they are including a lot of training data labeled with the language.
"how to say X in language Y" is a different task from saying X in language Y
The training data and the Apertus LLM may contain or generate information that directly or indirectly refers to an identifiable individual (Personal Data). You process Personal Data as independent controller in accordance with applicable data protection law. SNAI will regularly provide a file with hash values for download which you can apply as an output filter to your use of our Apertus LLM. The file reflects data protection deletion requests which have been addressed to SNAI as the developer of the Apertus LLM. It allows you to remove Personal Data contained in the model output. We strongly advise downloading and applying this output filter from SNAI every six months following the release of the model.
> Fully open model: open weights + open data + full training details including all data and training recipes
There are equally open, much more useful models out there: https://artificialanalysis.ai/?models=nvidia-nemotron-3-ultr...
How many normal people do you know who use "ChatGPT"? A lot, probably.
How many even know what "Gemma" is, let alone have downloaded llama.cpp, a GGUF file from Hugginface, and run "llama-server" from a text console with all the correct command arguments? How many are thinking about this use case when speccing out their next computer? Where is the breathless marketing copy boasting x tok/s?
We are sleepwalking into slavery.
Yes, I realise this isn't "running a local model", but it's using models that can be grabbed and run locally. For my pipelines, I feel far more confidence when I use an open model (even one like GLM-5.2 that would be expensive for me to run) since I have a backup plan if the hosted/cloud option becomes unworkable for me. If that happens to me with Opus, I have zero options.
This choice is made for us. The deciding factors will be convenience and economics.
My sense is that just like Web 2.0 SaaS we are destined for servitude.
A better strategy is to play an assymetrical game IMO. Don't let your would-be master write the rules by which you play.
What do you mean by this? Do you have an example in the given context?
You would also be shocked what's possible on a 64GB Mac Studio, which isn't that unattainable.
I can see this as a future battleground but access to frontier models (which you cannot run locally) seems a lot more relevant today.
Of course the frontier will always be unattainable, but that's like pointing out that I couldn't buy my own Cray supercomputer.
Yep. I'm an old time Linux sysadmin, but I am COMPLETELY baffled as to what I can or cannot run on my 32GB R9700 with 128GB main CPU memory.
If I want something Claude or Codex like what do I use that would be useful? If I want a chat system, what do I use? Images--apparently ComfyUI for setup but after that what do I do?
I don't even mind spinning up something in the cloud for a bit, but I need to know how I'm going to get data up and down without racking up massive bandwidth charges.
I'd love to do some tinkering, but the field is moving so fast and so full of charlatans that cleaning the dross out is almost impossible.
Who confirms those requests are legit?
the swiss have no gpus
I can run the 8B version of this swiss-ai model on a ten year old GPU. For the larger one, $2000 consumer hardware can run it fine. Beyond that, there are plenty of places where time on a GPU can be rented, and if the model is good, there will be hardware to run it.
There were a number of use cases where we needed to use Gemini (audio modality), and Ultra has been a VERY cost-effective alternative once we got through the nuances.
I think a problem with open-weight models is that while you can improve them, you are not going to create the next generation of LLMs by fine-tuning. We are at the mercy of frontier labs for access to SOTA LLMs. For example, Anthropic recently started requiring identity verification for Claude [0], same for OpenAI [1].
If one day China's distillation labs stop releasing their LLMs as open-weight, I doubt American labs will continue to release free LLM weights without that competition.
That's where fully open pipelines shine: they enable the community to create the next generation of SOTA LLMs. That is the only way LLMs truly become sovereign.
This notion that Chinese labs are merely distilling frontier models is quite an unwarranted slur. Those labs have published WAY more useful research than US labs on RL techniques, novel model architectures, training pipelines, etc. They have also hit intelligence-per-parameter densities that US labs have yet to attain.
Apart from that, merely training a model on outputs from another model, off policy and without the logits, doesn’t really work that well.
The Chinese labs know how to build frontier level models. GLM-5.2 shows that they no longer even need Nvidia chips to do it.
Chinese labs are basically just telling everyone, out in the open, what they're doing and how to do it, and the answer from American frontier labs is "Well, they couldn't possibly be getting the results they're getting without just distilling our models," and the American labs aren't even trying to do some of the stuff like DS's aggressive caching to get costs down.
it happens to all models…when the internet is increasingly generated, things happen
I disagree with this use of SOTA, and this topic is why.
Anthropic and OpenAI have “cutting-edge” models. These are beyond the state of the art but they are closed, secretive, hard to quantify.
The “state of the art” is open source, open weights models that can be inspected, studied, shared and critiqued, because that is what is meant by “the art” —- it is the knowledge and principles and evidence and materials available to all. The “state of the art” is the highest point of that.
I wish we could make this distinction and stop blessing two secretive, unverifiable loss-making companies with so much power.
(Putting that aside, I suspect — without evidence, mind you - that the endless march to solving models by making them bigger is not the solution anyway.)
Chinese's model like GLM is getting better for coding task and its cheaper. Microsoft Github copilot have to switch billing to token based. the cost of AI have increased since agent come into play. whoever can offer cheaper token to do task will win.
even Microsoft is looking into Deepseek for cheap token.
https://www.axios.com/2026/06/16/microsoft-copilot-cowork-to...
But "state of the art" implies the highest state of general availability, not just in terms of access to some product, but of use of the ideas, concepts, methodologies etc.
Anthropic and OpenAI have "cutting edge" models; the state of the art is behind the cutting edge.
The state of the art is the best open source, open weights model available. More or less by definition.
I am probably tilting at windmills here.
But the way SOTA is generally understood by other users of the language, it refers to exactly the team, technology, & techniques defining the cutting edge in any field, regardless of the whether the technology & techniques are available outside of that team...
its things you would be trained in as part of a bachelor's degree and some graduate coursework