The initial setup cost for running DeepSeek on-premise versus cloud hosting differs significantly due to several factors, including hardware requirements, scalability, and maintenance needs.
On-Premise Setup
- Hardware Costs: Running DeepSeek on-premise requires substantial upfront investment in hardware. The cost of AI acceleration hardware alone can be around $250,000, although this figure can be reduced by using less powerful GPUs[3]. A server capable of running the complete DeepSeek-R1 model in-memory can cost over $100,000[3]. Additionally, there are costs associated with purchasing software licenses for operating systems, databases, and other applications, which can add to the initial expense[2].
- Installation and Infrastructure Costs: Implementing an on-premise solution involves installation expenses, including physical setup, configuration, and testing. There are also costs for setting up the necessary physical infrastructure, such as cooling systems, power supply, and physical security measures[2]. These costs can vary widely depending on the size and complexity of the infrastructure.
- Maintenance and Control: On-premise solutions offer full control over data, hardware, and software but require ongoing maintenance costs, including hardware maintenance and IT staff salaries[6]. This can lead to higher operational expenses over time.
Cloud Hosting
- Initial Setup Costs: Cloud solutions typically have minimal initial setup costs, as they operate on a subscription model. The primary expenses include configuration, integration with existing systems, and data migration, which are generally lower than on-premise setup costs[2]. However, these costs can add up depending on the complexity of the migration.
- Scalability and Flexibility: Cloud hosting offers easy scalability, allowing resources to be adjusted as needed. This flexibility is particularly beneficial for dynamic workloads or startups[2]. Cloud services also provide managed infrastructure with security updates, reducing the need for a dedicated IT team for maintenance[8].
- Cost Structure: Cloud solutions follow a pay-as-you-go model, which means costs are operational expenditures (OpEx) rather than capital expenditures (CapEx). This approach allows for more predictable and flexible cost management, as costs are directly tied to usage[2]. For example, running DeepSeek-R1 on Azure could cost around $46,000 annually, depending on usage patterns, and this figure can be reduced with long-term commitments[3].
In summary, on-premise setups require significant upfront investments in hardware and infrastructure but offer long-term cost savings and full control over data and systems. Cloud hosting, on the other hand, provides flexibility, scalability, and lower initial costs but involves ongoing operational expenses based on usage. The choice between these options depends on specific needs regarding scalability, control, and budget constraints.
Citations:
[1] https://www.reddit.com/r/selfhosted/comments/1ibl5wr/how_much_money_would_i_need_to_run_r1_deepseek/
[2] https://forgeahead.io/2024/06/28/cost-comparison-cloud-vs-on-premise/
[3] https://www.computerweekly.com/news/366619398/DeepSeek-R1-Budgeting-challenges-for-on-premise-deployments
[4] https://s-pro.io/blog/cloud-computing-vs-on-premises-advantages-disadvantages-and-cost-comparison
[5] https://appinventiv.com/blog/cost-to-build-an-ai-app-like-deepseek/
[6] https://www.avahitech.com/blog/cloud-vs-on-premise-cost-comparison-guide
[7] https://play.ht/blog/deepseek-pricing/
[8] https://www.oneclickitsolution.com/centerofexcellence/aiml/on-premises-vs-cloud-hosting-llms-deepseek-r1-comparison