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

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Schlagbohrer 3 hours ago | parent | next [-]

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.

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nicman23 3 hours ago | parent | prev [-]

i mean qwen3.8 is a technical marvel

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walrus01 3 hours ago | parent [-]

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.

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nicman23 3 hours ago | parent [-]

it "fits" in 64 ram with mmap. granted it runs at 15 tk/s with a 9070xt but it runs

	▲	walrus01 3 hours ago \| parent [-]
		Right, I meant "fits" in the sense of I can load the whole thing into some combination of system RAM and GPU at llama-server launch. 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.