Found a way to cool the DGX
Summary
A user reports successfully using tap water to cool a DGX server while running the Qwen3.5-122b model at high GPU utilization, maintaining safe temperatures.
Similar Articles
Stop wasting electricity
The author demonstrates how to reduce RTX 4090 power consumption by up to 40% while running quantized Qwen models via llama.cpp, without sacrificing inference speed. By capping GPU power limits through nvidia-smi and adjusting llama-server parameters, users can significantly lower heat, noise, and extend hardware lifespan.
Dual dgx spark (Asus GX10) MiniMax M2.7 results
User benchmarks dual Asus GX10 (DGX Spark) running MiniMax-M2.7-AWQ-4bit, achieving 30–40 tokens/s while drawing only ~100 W each, replacing noisy multi-GPU rigs.
Tried Qwen3.6-27B-UD-Q6_K_XL.gguf with CloudeCode, well I can't believe but it is usable
User reports surprisingly usable coding performance from Qwen3-27B-UD-Q6_K_XL.gguf running locally on RTX 5090 at ~50 tok/s with 200K context, marking a significant leap in local model quality.
Finding the 4x 3090 Sweet Spot
A user shares power limit testing on a 4x RTX 3090 setup running Qwen3.6-27B with vLLM, finding 220W as the sweet spot for peak efficiency with minimal throughput loss.
RTX Pro 4500 Blackwell - Qwen 3.6 27B?
A developer shares local inference benchmarks and systemd configurations for running the Qwen3.6-27B model on an NVIDIA RTX Pro 4500 Blackwell GPU using llama.cpp. The post requests optimization tips for throughput and explores potential use cases for larger models.