Developer releases LLM Speedtest, an open-source desktop app for benchmarking local LLM inference
A user with an RTX 5090 and 96GB RAM asks whether Windows 11 or Linux is better for running Qwen3.8-27b, seeking the optimal inference server. The community discussion centers on maximizing performance for this model on high-end consumer hardware.
A user with an RTX 5090 and 96GB RAM asks whether Windows 11 or Linux is better for running Qwen3.8-27b, seeking the optimal inference server. The community discussion centers on maximizing performance for this model on high-end consumer hardware.
Port Visualizer is a free, open-source Windows application that visualizes which process owns each TCP/UDP port, how it's exposed, and what's changing over time. It helps developers and AI agent users identify and clean up stray processes and ports left by AI tools, with optional knowledge packs to recognize local AI services like Ollama, LM Studio, llama.cpp, and vLLM.
Port Visualizer is a free, open-source Windows application that visualizes which process owns each TCP/UDP port, how it's exposed, and what's changing over time. It helps developers and AI agent users identify and clean up stray processes and ports left by AI tools, with optional knowledge packs to recognize local AI services like Ollama, LM Studio, llama.cpp, and vLLM.
Oriveo is an open-source, bring-your-own-key chat client that connects to many LLM providers from a single app on iOS, Android, and the web. It uses LLMs via user-supplied API keys to OpenAI, Anthropic, Google Gemini, and others, plus local endpoints like Ollama. It solves provider lock-in and privacy concerns for users who want one self-hostable client with no accounts or subscriptions.
Oriveo is an open-source, bring-your-own-key chat client that connects to many LLM providers from a single app on iOS, Android, and the web. It uses LLMs via user-supplied API keys to OpenAI, Anthropic, Google Gemini, and others, plus local endpoints like Ollama. It solves provider lock-in and privacy concerns for users who want one self-hostable client with no accounts or subscriptions.
Reddit user benchmarks llama.cpp vs llamafile vs LM Studio vs Ollama across Metal/Vulkan/CUDA machines
Reddit user benchmarks llama.cpp vs llamafile vs LM Studio vs Ollama across Metal/Vulkan/CUDA machines
A practical guide to running LLMs locally with Ollama
A practical guide to running LLMs locally with Ollama