Latrix
Run, Secure, and Govern All Local AI.
To bring standardization, portability, and trust to the world of local AI.
An open-source, unified AI bridge runtime that provides a solid foundation for execution, security, and governance for all AI models on all devices.
Built by top global open-source contributors and trusted by next-generation AI application frameworks.
One Ecosystem, Two Cores
Latrix Runtime
The Core Execution Engine
We ended the "local AI environment hell". Latrix Runtime is a unified, OpenAI-compatible runtime that smooths over all underlying differences through intelligent hardware scheduling and automated inference optimization.
- ✓Multi-backend bridging: Seamlessly connect llama.cpp, vLLM, ONNX and more
- ✓Performance multiplier: Built-in speculative decoding, get 2x+ performance boost out of the box
- ✓One-click deployment: latrix pull, manage models as easily as using Docker
- ✓Unified governance: Built-in auth, rate limiting, monitoring & auditing for enterprise deployment
Latrix Secure
The Trust & Safety Layer
We bring order and trust to the chaotic world of open-source models. Latrix Secure is the industry's first evaluation and hardening platform focused on local AI security, providing "constitutional-grade" protection for your data and privacy.
- ✓Automated security assessment: Based on CARE benchmark, comprehensive "AI health check"
- ✓Threat detection & protection: Real-time model behavior monitoring, intercept potential risks
- ✓"Works with Latrix" certification: Build a trusted AI model and application ecosystem
- ✓Human ultimate control: Built-in "big red button" mechanisms, ensure AI is always under your control
Open Source & Research Integration
The birth of Latrix is inseparable from the wisdom crystallization of the entire open-source community and academia.
Open Source Technology Integration
Research Paper References
- Beyond GPT-5: Making LLMs Cheaper and Better via Performance-Efficiency Optimized Routing
- Empowering LLMs with Logical Reasoning: A Comprehensive Survey
- Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples
- Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
- Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs
- Pangu DeepDiver: Adaptive Search Intensity Scaling via Open-Web Reinforcement Learning
- Agent Learning via Early Experience
- Selective ion transport of nonlinear resistive switching by hierarchical nanometer-to-angstrom channels for nanofluidic transistors
- Breaking the Sorting Barrier for Directed Single-Source Shortest Paths
- Less is More: Recursive Reasoning with Tiny Networks
- DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation
- Video models are zero-shot learners and reasoners
We express our highest respect to all open-source projects, research papers, and thinkers who have provided "sparks of thought" and "solid code" for Latrix. We firmly believe that gratitude and reverence are the greatest part of the open-source spirit.