Top 50 Ai Gpu Cloud in Asia

This company offers a cloud platform optimized for the entire AI lifecycle, from model development and training to deployment. Their AI supercloud provides scalable computing resources, workflow automation, and performance monitoring to accelerate AI innovation for businesses.

Exabits specializes in refining raw GPU assets from leading manufacturers to support advanced AI infrastructure. The company provides access to high-demand hardware, including GB200s, H100s, H200s, and RTX5090s. This focus ensures that organizations have the necessary compute power for demanding AI workloads and innovation.

Aethirs provides a decentralized cloud infrastructure that delivers on-demand access to enterprise-grade GPUs for AI model training and real-time gaming applications. This solution addresses the need for scalable, low-latency compute resources while ensuring high performance and security across a global network.

Rutilea provides an AI development platform and GPU cloud services that facilitate the selection, development, and deployment of tailored AI models in a secure environment. The platform enhances operational efficiency by enabling businesses to implement AI solutions that streamline processes and improve decision-making.

The startup offers a blockchain-based platform that enables global sharing and utilization of GPU resources. This approach addresses the inefficiency of underutilized computing power, allowing users to access and monetize excess GPU capacity effectively.

Gongji Technology is a platform that utilizes distributed computing power and advanced scheduling algorithms to optimize resource allocation for AI applications. It provides flexible, on-demand access to high-performance GPU resources, enabling developers to efficiently manage costs and scale their computing needs without the complexities of server management.

Shansi Kaiwu provides a GPU Cloud platform built on heterogeneous multi-core architecture, specifically designed for high-performance computing (HPC) and artificial intelligence (AI) applications. The company offers scalable infrastructure that supports complex computational tasks, enabling efficient model training, fine-tuning, and inference across various industries.

The startup operates a cloud-based computing platform that provides AI-driven solutions for researchers and enterprises, focusing on large language model development, programmatic data labeling, and machine learning testing. It offers high-performance computing resources, including access to powerful GPUs and virtual machines, while promoting e-waste reduction through environmentally friendly practices.

The startup offers a cloud-based platform that optimizes AI infrastructure and workloads through the integration of open-source tools and resource estimation. This platform enhances operational efficiency by improving the deployment process of artificial intelligence applications for businesses.

Run:ai is an AI cluster management platform that optimizes GPU resource utilization through dynamic scheduling, GPU fractioning, and workload management. It enables organizations to increase AI workload efficiency by up to 10 times, accelerating development and reducing operational costs.

PinGo utilizes AI, decentralized physical infrastructure networks (DePIN), and GPU technology to enable users to monetize idle GPU resources for AI model training. This platform addresses the high costs and accessibility issues associated with computational power, allowing users to contribute to and benefit from a global network of GPU resources.

Edge Matrix Computing operates a decentralized AI infrastructure that utilizes a GPU-based distributed computing network to provide scalable computing resources for AI applications. This platform addresses the inefficiencies of centralized computing by enabling developers to deploy and manage AI dApps with reduced latency and improved resource allocation.

This company provides a Vision AI Engine specifically designed for automated cosmetic defect detection on automotive production lines. The system integrates without requiring line redesign, enabling real-time, sub-millimeter accurate inspection at every manufacturing stage. They also offer an end-to-end AI development platform for building and deploying intelligent industrial applications.

The startup develops an AI-driven decentralized computing platform that integrates blockchain technology with edge computing protocols, enabling users to share computing resources and process data efficiently. By utilizing smart contracts and decentralized storage, the platform enhances transaction verification and provides reliable computing power for decentralized applications (dApps).

ProjectX offers Infinity, a cloud-native operating system delivered entirely through the browser for high-performance computing. This platform enables users to run GPU-accelerated applications like Blender and VS Code instantly without downloads or virtual machines. Infinity abstracts compute resources, providing elastic GPU scaling and persistent environments for AI workflows, design, and development across any device.

Creative Humans AI provides AwasmCloud, a supercomputing platform that abstracts infrastructure to deliver on‑demand, low‑latency compute for real‑time AI and AGI workloads. The service automates deployment, scaling, and runtime orchestration, allowing engineers and enterprises to focus on model development rather than resource management.

Bitdeer provides digital asset mining services utilizing high-performance computing to optimize the mining process for cryptocurrencies. The company enables clients to efficiently access and manage mining resources, reducing operational costs and increasing profitability in the competitive blockchain landscape.

Style3D provides a cloud‑based platform that uses generative AI to turn 2D fashion sketches into fully simulated 3D garments, automatically generating patterns, trim specs, and photorealistic renders. GPU‑accelerated deformable body simulation enables fit assessment without physical samples, while a centralized asset library with version control supports real‑time collaboration, style tracking, and inventory visibility for designers, brands, and manufacturers.

Simplismart provides a high-performance inference engine that enables rapid deployment and fine-tuning of generative AI models on-premises or across various cloud platforms. This technology reduces model deployment time from months to days, significantly lowering operational costs while enhancing inference speed and scalability.

Avalanc offers a low-code AI platform designed to streamline deep learning development, enabling users to create and deploy models with minimal coding effort. This tool addresses the complexity and time constraints associated with traditional deep learning workflows, allowing teams to accelerate their projects significantly.

VESSL AI offers an end-to-end MLOps platform that enables machine learning teams to build, train, and deploy models efficiently across various infrastructures with a single command. The platform addresses the challenges of resource management and deployment speed by providing serverless deployment, real-time monitoring, and automated CI/CD workflows.

Inferless provides a serverless GPU platform that enables rapid deployment of custom machine learning models from various sources, including Hugging Face and Docker, while automatically scaling resources to handle unpredictable workloads. This solution reduces operational costs by up to 90% and eliminates the complexities associated with traditional GPU clusters, allowing businesses to efficiently manage their machine learning inference needs.

Vastai Technologies develops high-performance AI chips specifically designed for computer vision and video processing, including the SV100 series for cloud-based inference and the VE series for edge computing. Their technology addresses the need for efficient, low-latency video analysis and processing in applications such as real-time video streaming and industrial automation.

Provides a SaaS platform utilizing artificial intelligence to optimize resource allocation in cloud computing environments. By analyzing usage patterns and predictive modeling, it addresses issues of cost inefficiency and resource underutilization, enabling users to achieve up to 30% savings on cloud expenditures while improving system performance.

Provides an AI-driven platform for optimizing deep learning models through techniques like model compression, pruning, and heterogeneous scaling. This enables businesses to reduce GPU computing costs by up to 80%, achieve up to 6x faster inference speeds, and deploy resource-efficient models on edge devices while ensuring data privacy and security.

Luchen Technology provides a platform for training and deploying large AI models, significantly reducing training and inference costs by up to 90% while enhancing model capacity and speed. Their solutions enable businesses to efficiently build high-quality AI applications with minimal resources, streamlining the development process across various hardware environments.

Liansu Technology designs and develops high-performance GPUs for graphics rendering across devices, cloud, and automotive applications. Their focus is on creating domestically-produced GPU chips based on proprietary architecture to serve applications like gaming, digital twins, VR/AR, and professional design.

The startup develops a cloud-based platform that provides a secure digital workspace for organizational users, integrating hardware and software solutions with ongoing maintenance support. This technology addresses the need for secure and efficient collaboration in remote work environments, ensuring data protection and operational continuity.

Kluisz provides an AI-native cloud infrastructure platform designed for the AI era, aiming to reduce operational overhead and accelerate deployments. The platform autonomously builds, optimizes, and manages infrastructure while enforcing Zero Trust security protocols. It offers unified cloud services engineered to handle complex AI workloads without the typical hyperscaler complexity.

LOCI is an AI‑driven observability platform that analyzes compiled CPU and GPU binaries, using a hardware‑aware large code language model to predict performance and power hotspots before test or inference runs. It automatically rewrites binaries and adjusts runtime configurations, integrating with CI/CD pipelines to provide measurable throughput and energy savings for AI/ML and performance engineering teams.

Rebellions develops AI accelerators that utilize HBM3e chiplet architecture and 5nm System-on-Chip technology to enhance energy efficiency and computational performance for deep learning applications. The company addresses the need for scalable and efficient AI inference solutions in the rapidly growing generative AI market.

Ripple Software provides liquid-cooled computing power infrastructure designed for artificial intelligence-generated content (AIGC) applications. This technology enhances thermal efficiency and performance, addressing the high energy consumption and heat management challenges faced by data centers.

Krutrim provides an AI computing infrastructure and AI-powered applications tailored for the Indian market, enabling businesses to leverage machine learning and data analytics. This platform addresses the need for accessible and scalable AI solutions, enhancing operational efficiency and decision-making capabilities for local enterprises.

4Paradigm provides an AI enablement platform that delivers industry‑specific large models built from multi‑modal data and a software‑defined compute layer that abstracts hardware for high‑throughput, low‑cost processing. The platform includes AutoML, transfer‑learning tools, and a generative‑AI development suite that automates model creation, code generation, review, and deployment, all delivered via secure, GDPR‑compliant cloud services.

Hammerspace provides an automated data orchestration system that unifies and manages unstructured data across edge locations, data centers, and public cloud environments using a standards-based parallel file system architecture. This technology eliminates data silos, enabling organizations to optimize resource utilization and accelerate access to critical data for AI and high-performance computing applications.

Cloudwalk offers an AIoT platform that integrates edge devices, a collaborative operating system (CWOS), and multimodal foundation models to provide on‑device inference and standardized APIs for vision, speech, and language processing. The solution includes privacy‑computing, data‑governance, and AI‑Agent tools, allowing large enterprises and public agencies in finance, manufacturing, energy, and smart city domains to deploy AI capabilities without extensive custom integration.

HyperAccel engineers specialized AI semiconductors, utilizing a novel LPU architecture designed for high-performance and energy-efficient Generative AI workloads. Their product line spans from edge devices to cloud datacenters, offering optimized solutions for LLM inference. The company supports leading AI frameworks through a dedicated software platform, ensuring seamless integration for developers.

The startup develops an artificial intelligence platform that integrates machine learning, deep learning, natural language processing, image analysis, and computer vision to enhance operational efficiency across various sectors. By leveraging data analytics, the technology enables clients in health and beauty industries to optimize decision-making and improve customer engagement.

NeuReality designs AI-centric infrastructure that integrates a network addressable processing unit (NAPU) with purpose-built software to streamline AI inference workflows. This solution reduces reliance on traditional CPUs and networking components, addressing the complexity and inefficiencies that hinder AI model deployment and scalability.

FuriosaAI develops the RNGD data center accelerator, utilizing a Tensor Contraction Processor architecture to enhance the efficiency of AI inference with a power profile of just 150W. This technology enables enterprises to deploy large language models and multimodal applications with low latency and high throughput, significantly reducing energy consumption and operational costs in data centers.

Zafar SoftTech provides AI-powered SaaS platforms and custom AI tools that streamline business operations for SMBs. Their solutions automate tasks like email management, financial operations, and HR processes using technologies like NLP and machine learning. This helps businesses improve productivity, efficiency, and decision-making.

Homebrew develops local AI solutions, including the Jan AI Assistant and the Ichigo real-time voice AI, utilizing energy-efficient hardware to enhance performance. The company addresses the need for accessible, efficient AI tools that operate without reliance on cloud infrastructure, ensuring user privacy and reducing latency.

Cluster Systems designs high-speed interconnection solutions for data centers, utilizing PCIe and CXL switch technology to enhance GPU and CPU connectivity. Their products address the challenges of data transmission in large-scale computing environments, significantly reducing interconnect costs and power consumption.

Ivcloud provides a global interactive video cloud service that delivers ultra-high-definition, low-latency video streaming for applications such as cloud gaming and video conferencing. By shifting intensive visual computing tasks to powerful cloud servers, Ivcloud enables a wide range of devices to access immersive experiences without requiring high-end hardware.

This company offers a decentralized cloud platform with Kubernetes cluster management, storage, and automated DevOps tools. Their services cater to businesses needing solutions for AI/ML acceleration, data privacy, and content distribution within a Web3 environment.

NextSilicon's Maverick-2 Intelligent Compute Accelerator (ICA) utilizes software-defined hardware to dynamically optimize performance for high-performance computing (HPC) and artificial intelligence (AI) workloads. This technology eliminates the need for extensive code rewrites, significantly reducing development time and enabling faster insights across various applications.

Zesty is a cloud infrastructure optimization platform that utilizes machine learning automation to provide real-time recommendations for resource allocation, significantly reducing cloud costs and waste. By automatically identifying underutilized resources and adapting to demand fluctuations, Zesty ensures organizations only pay for their actual usage while maximizing operational efficiency.

Qingwei Intelligent Technology designs and manufactures AI chips optimized for high-performance computing tasks in artificial intelligence applications. Their technology addresses the demand for efficient processing power in AI systems, enabling faster data analysis and improved machine learning capabilities.

The startup provides AI infrastructure and services that enable businesses to access and implement machine learning models without requiring extensive technical expertise. By simplifying the deployment of AI technology, the company helps organizations leverage data-driven insights to enhance operational efficiency and decision-making.

Exlords develops an AI and machine learning-integrated hardware platform for edge processors, enabling real-time AI inference on user devices through on-device neural processing units. This technology addresses the need for efficient, localized computing solutions that enhance performance and connectivity in heterogeneous computing environments.