unsloth/DeepSeek-V4-Flash-0731-GGUF · Hugging Face
the quality of GLM 5.2 in just 155 or 162 GB?
https://huggingface.co/unsloth/DeepSeek-V4-Flash-0731-GGUFOpen linkView original on lemmus.orgSyndicated from the fediverse. Read and engage on the original instance.
View original on lemmus.orghttps://huggingface.co/unsloth/DeepSeek-V4-Flash-0731-GGUFOpen linkView original on lemmus.org
8 replies
Huh the unsloth Q4_K_XL variant running with 5-6 t/s on a 16GB 9070 XT, 128 GB RAM and an NVME ssd. This is shockingly usable 🤯
Did some more testing on it? This isnt a small model and i havent found the space to save it on my machines yet haha
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)
Wow, already unsloth quantizations available? That was fast.
Didn't even know they released the weights until just about now.
This will probably also mean that we will have alternative providers on Openrouter soon. Can't wait.
DS V4 will have a huge impact on many usecases. Dirt cheap and insanely capable, if only a part of the benchmarks translate to real life.
Increasingly interesting times for the big US AI companies, I guess...
Anyone knows, why 4bit quant is only marginally smaller than 8bit quant, though?
And shouldn't 8bit be roughly equal to the number of parameters anyway, so ~300GB?
the original model has a lot of parts that were natively trained in 4 bit, so those layers can't go higher
this appears to be the untouched model in GGUF format, 180 GB, MXFP4
https://huggingface.co/bartowski/DeepSeek-V4-Flash-0731-GGUF
Does antirez have new quants for ds4 ready?