NVIDIA DGX Spark

NVIDIA GPUs are a family of graphics processing units produced by NVIDIA Corporation, intended for graphics rendering, high-performance computing, and hardware acceleration of workloads such as machine learning and scientific computing. Major product lines include GeForce for consumer gaming, RTX A (formerly Quadro) for professional visualization, and data-center GPUs (e.g., A100, H100) for AI training and inference.

NVIDIA Blackwell is a family of GPU architectures and data-center GPU systems for generative AI and high-performance computing, including the B300 GPU platform. Blackwell systems can be deployed with Google Distributed Cloud to run Gemini and other AI workloads on premises.

mini-AGI is an experimental continual-learning, byte-level language model that trains from scratch on a CUDA-capable GPU with at least 8 GB of VRAM. It reads 256 byte values directly rather than using a conventional tokenizer, processes data one chunk at a time, and uses the same forward path for training and generation. Its architecture combines dense prelude blocks with a recurrent block applied up to 24 times, adaptive PonderNet-style halting, and per-application top-8 routing through a dynamically growing and pruning expert pool. Expert weights and Adam moments are stored as files on disk; a working set is paged through RAM and VRAM as needed, allowing the pool size to exceed available VRAM. The project includes Python commands for building corpora, reading files, streaming training, serving a local web interface, and inspecting or replicating continual-learning experiments. The repository describes the current model as toy-level rather than frontier-capable, and its weights are generated in the local weights directory rather than distributed with the source.

DwarfStar is a self-contained, model-specific native inference engine for running DeepSeek V4 Flash, GLM 5.2, and, on high-memory systems, DeepSeek V4 PRO locally. It combines model loading, prompt rendering, tool calls, persistent KV state, an HTTP server, and a coding agent rather than serving as a general GGUF runner. The engine supports Metal on Macs, CUDA including multi-GPU systems, and ROCm on Strix Halo hardware; it also provides SSD streaming for machines with insufficient RAM, distributed tensor and pipeline parallelism, and server-side micro-batching for multi-user inference. The repository includes tooling and data for GGUF, imatrix, quality, and speed testing, and acknowledges code and design contributions from llama.cpp and GGML.

A family of NVIDIA GeForce graphics processing units (GPUs) for consumer PCs and workstations, including hardware-accelerated ray tracing and AI processing through Tensor Cores. GeForce RTX GPUs are used for gaming, rendering, scientific and parallel computing, and workloads such as physical simulation and robotics development.