I feel like Ornith 1.0 9b was the best coding model at that size (since Qwen has neglected that size). Maybe now Ling Tiny is better but I'm curious to try Ornith 1.5
There are other ways investigators could have connected activity to Ono. He may have used Nyaa without a VPN while logged into an account. Data from website cookies or content-delivery-network logs could also have been matched with Nyaa activity and tracker records. CODA has not said whether any of those methods were used.
VPN isn't enough, you gotta worry about fingerprinting and cookies too. Recently it was revealed that Windows 11 has strong fingerprinting options that could be used to track you.
I wonder if they were using a VPN or seedbox. You could even do remote desktop into seedbox and browse the sites from there.
Old music doesn't get re-recorded for digital releases, they pull it from the original master again, which is better and more authentic than vinyl.
I mean if you went to a concert would you want them to add hiss and pop to the performance so it sounds more like vinyl? Lol certainly you wouldn't want them to intentionally worsen the signal-to-noise ratio
I've run Qwen 3.5 4b and Gemma 4 e2b on CPU only, this should be faster than those I think (fewer active parameters). If you have AVX512 or AVX10 then it should help a bit. Still slow compared to a GPU lol.
(Oops I got my Gemma and Qwen speeds mixed up, edited the post to fix it.)
But now with the new commits they added, with the same number of hot experts, Qwen is up to about 34. If I increase hot experts to 48 then I get around 37.
Gemma is still around 23 with just 10 hot experts. With 16 hot experts I get about 26 TPS. If I overprovision my VRAM (thanks to GGML_CUDA_ENABLE_UNIFIED_MEMORY=1) then 24 hot experts can give me 29 TPS, and 32 hot experts 34 TPS.
make sure that holds up with large context, you might need to step down to Q3 (which I've heard is still good for this model, many people are even using IQ2)
I feel like Ornith 1.0 9b was the best coding model at that size (since Qwen has neglected that size). Maybe now Ling Tiny is better but I'm curious to try Ornith 1.5
Sounds like you could just replace the template to fix it, there's a popular Qwen fixed template on hugging face, try that
https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates/blob/main/chat_template.jinja
https://huggingface.co/unsloth/Qwen3.8-2.4T-A95B-GGUF
just hoping for a new 35b a3b
I guess botched remasters aside lol, there isn't really a limit to how poorly something can be done
VPN isn't enough, you gotta worry about fingerprinting and cookies too. Recently it was revealed that Windows 11 has strong fingerprinting options that could be used to track you.
I wonder if they were using a VPN or seedbox. You could even do remote desktop into seedbox and browse the sites from there.
Old music doesn't get re-recorded for digital releases, they pull it from the original master again, which is better and more authentic than vinyl.
I mean if you went to a concert would you want them to add hiss and pop to the performance so it sounds more like vinyl? Lol certainly you wouldn't want them to intentionally worsen the signal-to-noise ratio
my laptop is crappy, so like 5 tokens per second lol, prompt processing of like 20 tokens per second
I think a decent laptop nowadays, even running CPU only, could probably do like 5x faster
I've run Qwen 3.5 4b and Gemma 4 e2b on CPU only, this should be faster than those I think (fewer active parameters). If you have AVX512 or AVX10 then it should help a bit. Still slow compared to a GPU lol.
anyone try this? this might be good for my crappy laptop lol
is it good enough to use with Zoo Code? is it better than Qwen 3.5 4b?
EDIT: woa
https://artificialanalysis.ai/models/ling-3-0-tiny
But not yet supported in llama.cpp https://github.com/ggml-org/llama.cpp/pull/26608
Actually funny he's not asking it to work harder (that would be system prompt or user message), he's forcing it to think that it will work harder
That's a really cool idea. It's like inception for an LLM, you make it think it was the one that thought of this lol
Have you tried preserve thinking? https://lemmus.org/post/24365786
(Oops I got my Gemma and Qwen speeds mixed up, edited the post to fix it.)
But now with the new commits they added, with the same number of hot experts, Qwen is up to about 34. If I increase hot experts to 48 then I get around 37.
Gemma is still around 23 with just 10 hot experts. With 16 hot experts I get about 26 TPS. If I overprovision my VRAM (thanks to
GGML_CUDA_ENABLE_UNIFIED_MEMORY=1) then 24 hot experts can give me 29 TPS, and 32 hot experts 34 TPS.👀
this has been a crazy few weeks! lol
true, it's not perfectly clear
also I just saw this
have you tried Qwen 3.6 35b a3b? check my guide, it's still relevant to you just with different numbers because you have 12GB
https://lemmus.org/post/24235317
Gemma is probably good for that, as long as it's consistently succeeding at the tool calls.
make sure that holds up with large context, you might need to step down to Q3 (which I've heard is still good for this model, many people are even using IQ2)
You're looking for "2160p remux" torrents