PulseAugur
EN
LIVE 09:04:48

NVIDIA Puzzle-75B-A9B model achieves high performance on consumer GPUs

A user on r/LocalLLaMA has detailed their experience running the Nemotron-3-Puzzle-75B-A9B model with NVFP4 quantization across three NVIDIA 3090 GPUs. The setup achieved 132 tokens/second with a 256K context window and FP8 KV cache, consuming approximately 500W. This configuration effectively utilizes the available VRAM, offering dense-class quality at speeds comparable to smaller models, a niche that the user notes is otherwise underserved in the current market. AI

IMPACT Demonstrates efficient use of consumer hardware for large models, potentially influencing future model design and hardware optimization.

RANK_REASON User-reported performance details of a specific model on consumer hardware, not a formal release or benchmark from the model's creators.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NVIDIA Puzzle-75B-A9B model achieves high performance on consumer GPUs

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Important_Quote_1180 ·

    NVIDIA Puzzle-75B-A9B NVFP4 at 132 t/s on 3×3090 — Why is this size category a desert otherwise?

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1uru9ja/nvidia_puzzle75ba9b_nvfp4_at_132_ts_on_33090_why/"> <img alt="NVIDIA Puzzle-75B-A9B NVFP4 at 132 t/s on 3×3090 — Why is this size category a desert otherwise?" src="https://preview.redd.it/edu2grao58ch…