It doesn’t matter.

What matters more is if firm’s start using a bundle of American and Chinese models and when they find their feet - how large is the market for frontier?

Frontier has to displace labour one for one at some point or it’s over.

I'm pretty sure the point of Qwen3.8-Flash-Next was to get the open source engines to integrate the qwen4 architecture.

The fact that it basically broke open the local model supremacy was just a nice side effect.

I'm running: https://github.com/peonist-ai/halogen-server with a quant4, PLE offloaded, and it's resident VRAM is 36GB at 265k context.

Shave 10 more GB off and the TAM openai and anthropic are targeting is a lost cause. Local models are what 90% of people will need.

If the world governments can get a handle on the memory cartel, then there's no more moat for most normal humans.

I wondered if there would be a Qwen 4 or we would go straight to 5, re: tetraphobia, but perhaps it's more like an uno reverse card in this case

https://en.wikipedia.org/wiki/Tetraphobia

Awesome 3.8 next runs great on my Framework Desktop so I'm loving more local models.

As soon as you can demonstrate decent financial returns (ie. the AI can run a company better than humans can), suddenly it makes sense to put a lot more $$$ in even if returns are diminishing - since whoever runs companies the best gets control of a big chunk of the world economy.

If you're actually applying LLMs, all of the things around the LLM that adapt it to coding, for example, that enable it to use existing validation tools for code, and enable it to diagnose and fix tool chain issues that aren't directly coding problems, are what makes the difference between a model that that scores a little higher on a coding benchmark and a model that's useful in a particular code base on a particular platform.

Are there any use cases that have enabled one customer of a frontier LLM to outperform a competitor using a different frontier LLM? Or is this why we are seeing confected points of comparison like solving challenge problems in mathematics?

I'm afraid it might be the other way around. RSI might pick all of the low hanging fruit soon. There must be a physical limit of how much intelligence you can squeeze out of some amount of parameters and compute.

There are going to still be worthwhile improvements but they are going to be more like not how to make transformers 10x cheaper but how to make next training run cost 9 trillions instead of 10 with a very particular optimization designed at the cost of hundreds of millions for this one specific run.

Don't worry, AI boosters will be in here soon denigrating anyone that uses anything but the latest and greatest models as irrelevant.

Build Nuclear, Build Thorium the Chinese are building whatever they can. They’re not locked in by special interest. Is that because they have lots of engineers on the job in government?

Training location is flexible. Iceland?

Europe has lots of zero-cost windows for electricity, and areas with cheap prices. The real issue is access to oil and gas.

France is actually pretty cheap in Europe. About 15% more than average USA electric prices (but I know that varies a lot across the states so still likely much more than the cheaper areas)