Infinigence AI

Overview

Infinigence is an enterprise-grade AI large-model service platform built specifically for developers of large-model applications. It focuses on delivering solutions for the AI 2.0 era, providing a powerful foundation for building, deploying, and scaling intelligent applications. The platform acts as an efficient deployment bridge between large models and a wide range of chips, enabling organizations to run advanced models on the hardware of their choice. This capability is fundamental to the infrastructure of the AGI (Artificial General Intelligence) era, where AI systems become more versatile and accessible across industries.

The platform offers a comprehensive computing-power inference platform, AI infrastructure solutions, and integrated on-device intelligence solutions. It supports more than 20 mainstream large models and over 10 different types of computing cards, ensuring broad compatibility across different hardware ecosystems. Through joint software-hardware optimization and unified deployment, Infinigence delivers high performance and operational simplicity, helping teams accelerate their AI initiatives. Whether used for cloud-based inference or edge deployment, the platform is designed to maximize efficiency and reduce the complexity of managing diverse AI resources.

Core capabilities

Intelligent Computing Cloud Platform

Provides one-stop services from compute power and models to applications, including cloud management, AI development, large-model development, and industry-specific models.

Domestic AI Compute Adaptation

Fully adapts 10+ domestic AI chips with 50%-200% performance gains via algorithm and compiler optimization, plus unified scheduling and mixed-precision computing.

Megrez-3B-Omni Model

The world's first open-source on-device omni-modal model, processing image, audio, and text, with Chinese/English voice input and seamless modality switching.

One-Stop AI Platform (AIStudio)

An enterprise-grade development platform for ML developers, offering dev machines, tasks, and full-lifecycle workflows from data hosting, coding, training, to deployment.

Computing Power Inference Platform

Provides heterogeneous resource management, O&M, monitoring, and a rich compute operations system.

Large-Model Service Platform (MaaS)

Offers fast, convenient model-calling APIs for data processing, fine-tuning, and inference, embedding best practices for model-app integration and toolified expert experience.

Heterogeneous Chip Hybrid Training Platform

First to support 1K-card hybrid training per task, 10K scalability, covering AMD, Huawei Ascend, Tianshu, Muxi, Moore Threads, NVIDIA.

On-Device Intelligence Solution (Model+Software+IP)

Provides integrated on-device solutions with software and IP, enabling efficient, unified deployment of multiple large-model algorithms on diverse chips.

Use cases

Quickly deploy an enterprise-specific intelligent customer service system in the cloud

Migrate locally trained large models to run on domestic chips

Provide low-latency inference services for content generation applications

Build a multi-chip hybrid computing pool to improve resource utilization

Optimize model inference performance on edge devices

Provide a unified large model experimentation platform for research projects