Aquiles-Image
A high-performance, memory-efficient inference server for diffusion models (image/video generation), compatible with the OpenAI client
Open source is how we build Aquiles-ai. We release models, datasets, and tools like Aquiles-Image and TinyQwen: open code anyone can use, audit, and improve. An open AI ecosystem isn't announced. It's built from day zero.

A high-performance, memory-efficient inference server for diffusion models (image/video generation), compatible with the OpenAI client
Is a high-performance Augmented Recovery-Generation (RAG) solution based on Redis, Qdrant or PostgreSQL. It offers a high-level interface using FastAPI REST APIs.
Drop-in sandbox component that executes AI-generated React code with zero configuration.
Extensible framework for creating and managing LLM function calling.
Understanding the Pipeline for Training an LLM from Scratch
Building a Multimodal Model with LFM2.5 and Kimi-K2.6