yeah, then theres prompt loading too.
but anyone who can fit QWEN-3.6 35B with a sustained ~30 token/s and ~100k context with cache could print money as a hardware vendor.
yeah, then theres prompt loading too.
but anyone who can fit QWEN-3.6 35B with a sustained ~30 token/s and ~100k context with cache could print money as a hardware vendor.
with llama-cpp and offloading non-active experts (from MOE architecture) to cpu RAM, you can easily run 50 tok / s QWEN-3.6 35B on 8-12 GB of VRAM. KV cache is a few GB, experts are ~3-5 GB (assuming q8 quant from Unsloth for example).
You can scroll through r/localllama and find tons of people getting useable speeds out of Qwen 35B.
24 tok / second on an ancient 1080ti
https://old.reddit.com/r/LocalLLaMA/comments/1tcc7h5/24_toks...
100 tok / second on a 4070
https://old.reddit.com/r/LocalLLaMA/comments/1tjh7az/110_tok...
That just sounds like a 3090.
not at the vram sizes that control how much context to load; also, GPUs arn't as effiecient as direct inference.