LocalIQ

LocalIQ is a high-performance LLM inference server designed for enterprise-grade deployment, enabling users to run and manage large language models (LLMs) with built-in load balancing, fault tolerance, and secure retrieval-augmented generation (RAG). It offers flexible deployment options, supporting both on-premise and cloud-based infrastructures. The platform is optimized for advanced LLMs, including models like DeepSeek-R1 for complex reasoning tasks and Qwen2.5-VL for multimodal processing of images and videos. LocalIQ provides comprehensive model management, allowing organizations to efficiently serve multiple LLMs, track versions, and integrate with existing applications via API endpoints. A key feature of LocalIQ is its two-component architecture: * Server – Functions as the central coordinator, handling API requests, worker management, and performance monitoring. * Workers – Dedicated processing nodes using NVIDIA GPU acceleration to handle LLM inference workloads efficiently. With intelligent workload management, LocalIQ dynamically balances inference requests, ensuring fault tolerance and optimal resource allocation across a distributed system. The web panel offers real-time performance monitoring, API token management, and an interactive chat interface for direct model interactions. Designed for scalability and enterprise security, LocalIQ allows organizations to maintain full control over their data, making it an ideal solution for businesses needing high-availability AI inference without reliance on third-party cloud providers.