Published: 2026-10-18
Visualizer for neural network, deep learning and machine learning models
WeeLLM runs large diffusion models with as little as 4 GB of VRAM, without any quantization. It dynamically determines how many layers can fit within the available VRAM and streams the text encoder and transformer layers to the GPU layer by layer, enabling inference on hardware with limited VRAM. It supports both safetensors and GGUF models.
Simple, safe way to store and distribute tensors
Native Rust inference server for open models on NVIDIA and Apple Silicon. OpenAI- and Anthropic-compatible APIs, GGUF + safetensors + MLX, FP8/NVFP4/MXFP4/Q8/Q4, built-in Studio
A tiny neural-network framework in pure Go with AVX2 SIMD kernels (GOEXPERIMENT=simd)
Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore.
Chatpin puts your AI’s chat template under inspection and lock. Compare it with the publisher’s original, flag suspicious conditional logic, and pin the version you trust so unexpected changes fail CI before deployment. Built for GGUF and safetensors workflows. Your model has a chat template. Give it a tamper alarm.
Native ComfyUI nodes for SenseNova U1.5 image generation and multi-reference image editing.
Local LLMs that run lean, load instantly and keep getting smarter. A from-scratch runtime + model format in Zig: zero-copy mmap, CPU/CUDA/Vulkan engines, OpenAI-compatible server, 2:4 sparsity, Net2Net growth, in-file version history, self-learning loops.