Havuz

The Open Source Strix Halo AI engine. Qwen 3.8 Flash Next Q4_K_XL: 1,801.01 pp, 73.17 tg single user, 194.37 tok/s 8 users; Qwen 3.8 27B Q4

An agentic system that auto-optimizes LLM workloads on AMD GPUs.

Kyojin: open-source engine that runs the largest open models on one mini PC or one graphics card, about 2× faster than llama.cpp. AMD (ROCm)

halogen-flash-server, Qwen3.8-Flash-Next modelini AMD Strix Halo (gfx1151) donanımında çalıştırmak için özelleştirilmiş bir inference server'dır.

Neden yükseliyor · 32 günlük repo için 722 yıldız ve son 28 günde 99 commit dikkat çekiyor. README, belirli donanım üzerindeki ölçümleri ve ölçüm koşullarını açıklıyor; ancak performans iddiaları proje tarafından sunulmuş ve bağımsız doğrulama bilgisi burada yok. 99 commit'in tek yazardan gelmesi geliştirme hızını gösterirken bakım kapasitesine dair kanıtı sınırlıyor.

Evidence-backed AMD Strix Halo local-AI setup and benchmarks: Qwen3.8, Ollama, llama.cpp, Vulkan/ROCm, large GGUFs, and cross-OEM results.

The fastest way to run Qwen3.8 27B on Strix Halo (gfx1151)

An inference framework customized for AI MAX 395, compatible with both Linux and Windows, and supports deploying only qwen3.8-flash-next. Th

Instella MoE is a fully open state-of-the-art Mixture-of-Experts language model, trained end-to-end on AMD Instinct™ GPUs.

Dashboard for InferenceX™, Open Source Continuous Inference | InferenceX 仪表板

SGLang Docker image for AMD Strix Halo (gfx1151 / Radeon 8060S)

AI coding agent harness for any hardware, local or cloud (OpenAI-compatible engines). Tuned for AMD Strix Halo: Qwen3.8 125B on the iGPU, NP

Terminal fleet monitor for GPUs, NPUs, and 13 other accelerator kinds, from utilization down to which pod is using them.

WHIRL (Windows HIP Inference for RDNA LLMs): native Windows C++/HIP LLM inference engine for the AMD Ryzen AI Max+ 395 (Radeon 8060S) and Ra

HRX, LOOM, Mac, and AMD running top speed kernels with a self optimizing engine.

`roctop` is a small AMD ROCm GPU monitor. It shows GPU VRAM usage, utilization, temperature, and GPU processes in a refreshing terminal UI.

Run LLMs and Ollama Qwen across AMD XDNA1 NPU, CPU, and GPU on Ryzen AI Linux systems.

Self-hosted LLM/RAG stack in one command — AMD Strix Halo / x86_64 (ROCm/Vulkan, Docker Compose)

DeepSeek-V4-Flash inference for AMD Strix Halo

LLM inference engine for AMD RDNA4 — Rust + Vulkan compute shaders, gguf & native FP8.

Browser-based operator console for managing and monitoring Lemonade on Linux inference servers.

🔥 AI agent that ports CUDA code to AMD ROCm using local LLMs — FastAPI + React + Ollama | Live: rocmporter-agent.vercel.app

Multi-seat game streaming on Linux: several people play on one PC at the same time, each in an isolated container with their own Sway, Sunsh

Object-storage-native KV cache for LLM inference & RL. Cross-restart, cross-conversation, cross-engine via shared S3 bucket.

DeepSeek V4 Flash 284B on AMD Strix Halo (gfx1151) — up to 32 tok/s decode & ~250 tok/s prefill via ROCmFPX, DSpark & ROCm 7.2

Strata 0.2.3 (engine 0.1.48) for AMD gfx906 (MI50/MI60/Radeon VII): rocBLAS solution table, Qwen3.6/Ornith engine restored, DFlash2 build fi

PantheonSim: GPU simulator for CUDA and ROCm. Run CUDA and HIP programs unmodified on a CPU, no GPU needed: simulated NVIDIA and AMD GPUs fo

Model Dispatch and Memory Allocator: an LLM inference engine for the hardware you own. Custom CPU, ROCm, Vulkan, CUDA, Metal and Level Zero

Headless Steam Big Picture in a rootless Podman container, streamed to a Steam Deck or any Moonlight client. Shares your game library, not y

AMD Radeon 9700 AI PRO RDNA multi GPU Tools for llm/vLLM inference, tuning, overclocking, undervolting and LLM models benchmarking

Hybrid RAG over Indonesian legal documents (UU, PP, Perpres, court decisions) with local LLM via Ollama.

OptiScaler ILION — Community fork with bilingual ES/EN interface, FSR 4 version switching, live performance metrics and benchmarking tools.

Whisper-large-v3 fine-tune for Indonesian + Javanese + Sundanese ASR. Lhotse + k2 lattice rescoring pipeline.

Multimodal document QA: vision + retrieval over PDFs (LLaVA + LlamaIndex)

See every GPU in your lab in the terminal, the browser or a report — who holds each GPU, which ones sit idle. One Python file, nothing to in