Bitdeer

• GPU virtual machines for AI model training and inference workloads
• Dedicated bare-metal GPU servers with direct hardware access
• Container services for deploying and managing computing workloads
• Serverless AI model APIs for inference without managing model servers
• Distributed training jobs across multiple high-performance computing servers
• AI Agent Platform for building, deploying, and managing AI agents
• Access to NVIDIA GPU configurations, including H100, H200, B200, and GB200 systems
• On-demand and reserved computing options with usage-based pricing
• Scalable compute resources with configurable storage and networking
• API documentation, technical guides, and enterprise security certifications

What Is Bitdeer AI?

Bitdeer AI is a cloud computing and AI infrastructure platform developed by Bitdeer Technologies Group. It provides GPU-accelerated computing, AI model inference, distributed training, container services, and tools for deploying AI applications. The platform is designed for developers, researchers, startups, and enterprises that need computing resources for machine learning and other data-intensive workloads.

Bitdeer AI brings computing infrastructure and AI development services together in one environment. Users can select suitable hardware, deploy computing instances, access supported AI models through APIs, and scale workloads according to project requirements.

GPU Cloud Computing

GPU computing is a central part of Bitdeer AI’s offering. The platform provides access to GPU-equipped virtual machines designed for computationally demanding tasks, including deep learning, large language model training, inference, and scientific computing.

Users can select configurations based on their required GPU model, memory, computing capacity, and workload size. Available hardware includes NVIDIA H100, H200, B200, and GB200 systems, with specific configurations depending on availability and service type.

GPU resources can be useful for developing machine learning models, processing large datasets, running experiments, and serving AI applications. Actual performance depends on the selected hardware, software configuration, and workload.

Virtual Machines and Bare-Metal Servers

Bitdeer AI offers virtual machines that combine computing resources such as processors, memory, storage, networking, and GPUs. These instances provide a flexible environment for configuring and running AI workloads without managing physical hardware directly.

For projects requiring direct access to dedicated server hardware, the platform also provides bare-metal GPU services. Related capabilities include preconfigured operating system images, snapshots, floating IP addresses, block storage, and network security controls, depending on the service configuration.

Container Services

Container services allow users to run applications in containerized environments without managing every aspect of the underlying infrastructure. This approach can help development teams package software and its dependencies consistently across development and deployment workflows.

Container-based environments are useful for deploying machine learning applications, supporting repeatable experiments, and organizing workloads that need specific software dependencies. Available configuration and orchestration capabilities depend on the selected service.

Serverless AI Model Inference

Bitdeer AI provides access to a library of AI models through serverless inference APIs. This allows developers to submit supported requests to hosted models without independently provisioning and maintaining a dedicated model-serving environment.

The available model selection supports different AI tasks, including large language model applications and computer vision workflows. API-based access can help developers integrate AI capabilities into websites, internal tools, and software applications.

Model availability, request limits, pricing, and supported parameters vary by model and service. Developers should consult the current API documentation before integrating a specific model into a production workflow.

Distributed AI Training

For workloads that exceed the capacity of a single computing instance, Bitdeer AI supports distributed training jobs across multiple high-performance computing servers. Distributed computing can help teams allocate resources to demanding training tasks that require substantial GPU capacity.

This capability is relevant to machine learning researchers, AI developers, and organizations training or fine-tuning models. The overall training time depends on factors such as model architecture, dataset size, software optimization, networking, and the number and type of GPUs assigned to the job.

AI Agent Platform

Bitdeer AI includes an AI Agent Platform for building, deploying, and managing AI agents. Agent-based applications can use AI models to perform defined tasks and support multi-step workflows, depending on how each agent is configured.

The platform also describes solutions for enterprise AI agents, including centralized management and control. These capabilities can support organizations that want to move AI-powered workflows from experimentation toward managed deployment.

Flexible Pricing and Resource Scaling

Bitdeer AI offers usage-based computing options and longer-term reservations for supported GPU configurations. Pay-as-you-go pricing allows customers to select resources for particular workloads, while longer commitments may provide different hourly rates.

Pricing varies according to hardware, resource quantity, contract duration, and configuration. The platform also lists general-purpose CPU computing, storage, networking, and AI model inference as separately priced services.

New users may be eligible for US$5 in promotional credits for supported model inference, subject to the offer’s terms and validity period. GPU computing is generally charged according to the selected instance and billing arrangement.

Security and Infrastructure

Bitdeer AI describes a global AI infrastructure built to support scalable computing and AI deployments. Its platform highlights security and operational reliability, with ISO/IEC 27001:2022 certification and SOC 2 Type I and Type II reports.

Organizations evaluating the service should review its current security documentation, data handling policies, service-level commitments, and available access controls to determine whether the platform meets their requirements.

Who Can Benefit From Bitdeer AI?

• AI developers building and deploying machine learning applications
• Researchers running GPU-intensive experiments and model training
• Startups needing computing infrastructure without purchasing physical servers
• Businesses integrating hosted AI models through APIs
• Engineering teams deploying containerized applications
• Organizations building and managing AI agent workflows
• Enterprises requiring scalable computing resources for AI projects

Frequently Asked Questions

What is Bitdeer AI used for?

Bitdeer AI provides cloud infrastructure and AI services for model training, inference, distributed computing, containerized applications, and AI agent deployment.

Does Bitdeer AI offer GPU cloud servers?

Yes. It provides GPU virtual machines and bare-metal services with supported NVIDIA GPU configurations. Availability and pricing depend on the selected hardware and service.

Can developers access AI models through an API?

Yes. Its serverless model inference service provides API access to supported models, allowing developers to integrate AI capabilities without managing their own model-serving infrastructure.

Does Bitdeer AI have a free plan?

Its core computing services use paid pricing, but eligible new users may receive promotional credits for supported AI model inference. Promotional credits do not mean that GPU computing is generally free.

How much does Bitdeer AI cost?

Costs depend on the GPU model, number of resources, contract length, and service type. GPU computing starts at approximately $2 per GPU-hour for certain configurations, while other hardware options can cost more.

Who should consider Bitdeer AI?

It is intended for AI developers, researchers, startups, and enterprises that need scalable GPU computing, hosted model APIs, or infrastructure for deploying AI workloads.

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