NVFP4 vs FP8 vs GGUF on a 16 GB Ada GPU: NVFP4 decodes 2.3x faster and ties BF16 on GSM8KWhen you type «nvfp4 vs» into Google it completes with «fp8», «gguf», «q4_k_m» and «bf16». The usual answer compares different models quantized by different people. On October 16 NVIDIA released Nemot4d ago · 2 min readefraingaray.hashnode.dev
Kandinsky 6.0 on a 16 GB GPU: the official recipe runs out of memory, and only the 29B model passed my Spanish testKandinsky 6.0 generates five seconds of video with its audio, voices included, from a text prompt (MIT license). I wanted to know two things: does it run on a 16 GB card, and can it speak Spanish? MemOct 14 · 2 min readefraingaray.hashnode.dev
Qwen-Image 2.1 on 16 GB of VRAM, quantized to NF4: a real benchmark against FLUXOn a 16 GB RTX 4070 Ti SUPER, Qwen-Image-2.1-Turbo does not fit in bf16 (the pipeline is 32.5 GB). Quantized to NF4 with bitsandbytes it does, and I ran it against the FLUX.1-dev Q6_K + pixel-art LoRAOct 12 · 2 min readefraingaray.hashnode.dev