dual-gpu

KDE Plasma widget to change the GPU mode using the EnvyControl command line tool.

Qwen3.8-Flash-Next on 2× RTX 3090 + 128 GB RAM. Experimental peaks: 1,860 tok/s prefill at 260K input; 89.1 tok/s decode at 128K input. Full 256K context.

D-Bus service to check the availability of dual-GPU

Real-time N-Body Algorithm Accelerated With CUDA and FFT (for up to 1 billion particles with multi GPU)

Quality-first local MiniMax H3 video-series generation and loopback API for dual RTX 4090 workstations, with native audio, references, P8/P9 continuity, and preserved artifacts.

Dual RTX 3090 local LLM infrastructure — 48 GB VRAM AI cluster build. Hardware spec, photos, power-limit script. Companion to the blog series at blog.zacharycangemi.com.

Reproducible vLLM recipe for shawnw3i/Huihui-Qwen3.6-27B-abliterated-AWQ-MTP on 2× RTX 3090 in a Proxmox LXC. MTP n=3, 256K context, full vision+tool-calling+reasoning. Silent 24/7 operation at 250W per card. Companion to the base-model recipe.

Hybrid AI routing: LOCAL Ollama + CLOUD GitHub Copilot

Reproducible Mage-Flow-Turbo inference on Kaggle Tesla T4×2 using upstream PyTorch, BF16 dtype/materialization and SDPA. Includes canonical dual-GPU qualification, explicit transformer/VAE placement, fail-closed routing and provenance checks, sustained 12-image 512/768/1024 showcase, timing, GPU memory metrics, SHA-256 evidence, and bilingual docs.

Reproducible vLLM recipe for Qwen3.6-27B (AWQ-BF16-INT4) on 2× RTX 3090 in a Proxmox LXC. MTP, 256K context, full vision+tool-calling+reasoning. Bare-LXC alternative to Dzombak's Docker recipe. Benchmarks, gotchas, GPU passthrough config included.

Professional GPU Performance Testing Suite for dual GPU setup (AMD RX 6600 + NVIDIA RTX 3050) with comprehensive monitoring tools, crash-safe scripts, and thermal management optimized for ASRock X570 Taichi + Ryzen 7 5700X

Multi-GPU LLM benchmarking system with validation pipeline, continuous evaluation, and leaderboard UI

Native dual-GPU long-context inference runtime for Qwen3.8-Flash-Next

Dual-GPU LLM gateway with deterministic routing, agentic orchestration, constraint verification, and an Answer Quality Gate

GPU-aware system monitor for Windows. Per-process VRAM, dual GPU support, hardware controls. Single binary, Rust.

Containerized local LLM development stack. Features automated multi-GPU vLLM hosting (optimized for Qwen-Coder), | Tunables & Benchmarks │ One-click integration configurations for Zed IDE, VS Code Continue, and Aider CLI.