Mo Di Diffusion
Professional-grade modern 3D animation aesthetics powered by specialized Stable Diffusion fine-tuning.
The premier open-source ecosystem for local LLM inference and context-rich creative storytelling.
KoboldAI represents a critical infrastructure layer in the 2026 decentralized AI movement. It is a highly extensible browser-based front-end and back-end designed for high-performance inference of Large Language Models. At its core, KoboldAI bridges the gap between raw model weights (GGUF, EXL2, AWQ) and end-user creative applications. Its most significant technical achievement is the 'Lorebook' system—a sophisticated context-injection engine that allows users to define recursive world-building elements that are dynamically inserted into the context window based on keyword triggers. This prevents the 'memory loss' typical of standard LLM interactions. By 2026, the ecosystem has bifurcated into KoboldAI United (the feature-rich Python interface) and KoboldCPP (a lightweight C++ implementation for hardware-constrained environments). It supports a wide array of backends, including local GPU acceleration (CUDA, ROCm), CPU-only inference, and distributed compute through the AI Horde network. Its role in the market is to provide a privacy-focused, censorship-resistant alternative to proprietary APIs like OpenAI, offering developers and writers total control over their local inference pipeline and data sovereignty.
A recursive dictionary system that triggers context injection into the prompt based on specific regex or keyword matches.
Professional-grade modern 3D animation aesthetics powered by specialized Stable Diffusion fine-tuning.
The Open Source AI Knowledge Engine for the Modern Enterprise.
Efficient 3D mesh generation from single images using sparse-view large reconstruction models.
The open-source powerhouse for collaborative, model-agnostic blog generation and content strategy.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Ability to load small, trained vector layers over a model to shift its prose style without a full fine-tune.
Supports GGUF, EXL2, AWQ, and Transformers backends within a single unified interface.
Built-in client and host for a peer-to-peer network of LLM providers.
Includes Mirostat, Top-A, Typical Sampling, and Tail Free Sampling (TFS).
Allows for Jinja2-style templating to format prompts for specific instruction-tuned models (Alpaca, Vicuna, ChatML).
Caches the KV (Key-Value) states of the prompt to speed up subsequent generations.
Writers working on sensitive or proprietary IP cannot use cloud providers like OpenAI due to data harvesting concerns.
Registry Updated:2/7/2026
Dungeon Masters need an AI assistant for world-building in locations without stable internet.
Developers want to test LLM integrations without incurring thousands in API token costs.