3090

Using the famous cnn model in Pytorch, we run benchmarks on various gpu.

Read NVIDIA RTX 3090, 3080, 3080 Ti, 3070 Ti, 3060 Ti, 2080 Ti, 2080, A2000, A4000, A4500, A5000 GDDR6X and GDDR6 temperatures directly on HiveOS GUI

This small python script allows you to open links from PartAlert.net in the case you need a new GPU (or any hardware alert from PartAlert.net)

Field notes on hardware, local ML inference, and building things to understand them.

Gathering benchmarks for models that run on consumer hardware, particularly DGX Spark and 3090s

local-c8-worker: a DSH dual-model toolkit pairing a DeepSeek brain with a local Qwen3.8-27B worker (8192-token context, served by Don-Chad/ninfer-3090). Ships a deployer, presets, skills, and a fallback client; splits tasks into chunks, fans out, then aggregates and compacts.

Benchmarks from GPU's I've tested

local-c1: a DSH helper that registers a local Qwen (qwen3.8-27b) model on a 3090 node via one idempotent Node script—patches settings.yaml and the dual preset's compaction policy. Inference served by Don-Chad/ninfer-3090. Supports dry-run and auto-backup; restart DSH to apply.