FreeToken, a new inference engine from FlashML, lets users run frontier models on gaming GPUs at interactive speeds, with Qwen3.6 35B running on an 8GB RTX 4060 laptop at 39 tokens per second, DeepSee…
MiniMax H3, an open-weights AI video generator from Hailuo (MiniMax), can now run locally on GPUs ranging from an RTX 2060 with 6GB VRAM to an RTX 5090, with community users reporting generation times…
Spriteloom, a local AI pixel-art generator plugin for Aseprite, has been released, enabling users to generate, edit, and inpaint sprites entirely on their own GPU with no cloud or subscription. The to…
Nvidia at SIGGRAPH in Los Angeles detailed DLSS 5, its AI-powered graphics tool, promising to preserve 'artistic intent' after backlash at GTC earlier this year. The company demonstrated three model o…
Nvidia has not announced a successor to its RTX 5090 graphics card more than a year after its launch, and AI models ChatGPT, Perplexity, and Gemini suggest the company's focus on higher-margin AI and …
A developer built Aakaar, a deep learning framework from scratch using native C++ and CUDA, wrapped in Python. In a benchmark against PyTorch on EMNIST, Aakaar achieved slightly faster runtime while m…
NexSub, a fully offline AI video subtitle translator using local Whisper models, launches as the world's first tool to provide real-time multilingual subtitles without internet or cloud costs. It supp…
Flow, a compact data pipeline language designed to reduce token usage for large language models, achieves an average 33% token reduction compared to Python, according to developer Pinku. The open-sour…
A 35-billion-parameter Mixture-of-Experts model runs at 28 tokens per second with full 128K context on a 2019 gaming laptop with a GTX 1660 Ti and 6 GB VRAM using llama.cpp's --n-cpu-moe flag and Turb…
A developer has published a guide for setting up a local AI coding assistant in VS Code using Continue and Ollama, achieving tab autocomplete and code chat entirely on-device. The setup requires a GPU…
A developer provides a formula for estimating RAM requirements to run large language models locally, explaining that a 7B model at Q4 quantization needs roughly 4.2GB plus overhead. Benchmarks show th…