5 Cheapest Cloud Platforms for Fine-tuning LLMs

As the demand for training, fine-tuning, and inferring Large Language Models (LLMs) continues to grow, finding cost-effective cloud platforms has become crucial for researchers, developers, and businesses. These large models require high-end GPUs with substantial VRAM. For example, using AWS can easily cost around $8 per GPU per hour. Moreover, since these models often demand multiple GPU setups, costs can quickly escalate within a few hours.

To help mitigate these expenses, this blog post will compare five popular cloud platforms that offer competitive rates for LLM fine-tuning: Vast.ai, Together AI, Hyperstack, Cudo Compute, and Runpod. We will focus on their pricing, particularly for H100 and A100 GPUs, and discuss the features and benefits of each platform.

1. Vast.ai

 
Vast.ai stands out as the most affordable option for fine-tuning large language models. The platform operates as a marketplace for GPU rentals, providing a wide range of options at varying price points. However, you must request the GPU in advance to access them. Vast.ai also offers interruptible instances that can save an additional 50% or more on costs through spot auction-based pricing.  

• H100 SXM starting from $1.93/hr
• A100 PCIe starting from $0.64/hr

Features and benefits:

•   Consumer GPUs like the 5090 and 4049 are available at lower prices.  
•   Flexible enterprise GPU selection and configuration.  
•   The Marketplace model allows for competitive pricing.  
•   Scalable options for various project sizes.  

2. Together AI

 
Together AI offers competitive pricing for GPU usage, making it a strong contender for cost-conscious users. Unlike traditional cloud providers, Together AI functions as an AI company that provides affordable API access to open-source models like Llama 3.3. It also offers services for fine-tuning at a low cost, allowing you to train, fine-tune, and serve your model using the same platform.  

• H100 SXM starting from $1.75/hr
• A100 PCIe starting from $1.30/hr

Features and benefits:

• Request GPU clusters for testing.
• User-friendly interfaces and integration capabilities.
• Support for advanced fine-tuning techniques like transfer learning, LoRA, and RLHF.
• Focus on accessibility for teams with varying levels of technical expertise.

3. Hyperstack

 
Hyperstack is a cost-effective solution for cloud computing, focusing on providing scalable and affordable infrastructure for AI and machine learning tasks.  

• H100 SXM starting from $1.95/hr
• A100 PCIe starting from $1.35/hr

Hyperstack’s reserved pricing offers significant savings, especially for long-term projects, making them 75% more cost-effective than traditional cloud providers.  

Features and benefits:

• Reserve the GPU clusters to get an even cheaper price.
• Competitive pricing models for GPU usage.
• Discounts available under the NVIDIA Inception Program.
• Optimized performance for GPU workloads.

4. Cudo Compute

 
Cudo Compute is recognized for offering competitive rates and volume discounts for longer-term commitments. Users can rent high-performance cloud GPUs on demand and at scale for AI, machine learning, rendering, and more.  

• H100 SXM starting from $2.45/hr
• A100 PCIe starting from $1.50/hr

Features and benefits:

• Deploy instances with our dashboard or CLI tooling.
• Decentralized cloud platform.  
• Potential cost savings by leveraging underutilized computing resources.  
• dstack integration for container orchestration.  
• Strong focus on security and data privacy.  

5. Runpod

 
Runpod is my favorite and the easiest platform to use for data scientists. It offers competitive pricing for GPU instances, with both on-demand and spot options available. However, their pricing for H100 is slightly higher than some competitors.  

• H100 SXM starting from $2.79/hr
• A100 PCIe starting from $1.64/hr

Runpod’s pricing for the A100 is highly competitive, matching Vast.ai’s lowest rate. However, their H100 pricing is slightly higher than some competitors.

Features and benefits:

• Scalable GPU solutions with a focus on ease of use
• Support for various AI workloads
• Cost-effective options for enterprises

Conclusion

 
When it comes to fine-tuning LLMs, choosing the right cloud platform can significantly impact your project’s cost and efficiency. Among the platforms reviewed, Vast.ai emerges as the most affordable option, particularly for A100 GPUs, making it ideal for budget-conscious users. Together AI and Hyperstack also offer competitive pricing, with Together AI excelling in accessibility and Hyperstack providing long-term savings through reserved pricing. For those seeking decentralized solutions, Cudo Compute offers unique benefits, while Runpod is user-friendly and comes with documentation designed for data professionals.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.