Private LLMs vs ChatGPT API: Comparing the Cost-effectiveness (Private Deployed AI Models Part 3)

Welcome back! This is the final article in our series on private deployed models. In previous articles, we discussed the significant advantages of private models in terms of data security and customization.

For business leaders, cost efficiency is key when leveraging AI technologies. In this concluding article, we will explore the cost benefits of deploying private large language models (LLMs) on platforms like AWS, comparing them to the expenses associated with using open-source APIs like ChatGPT.

What Are Private LLMs?

Private Large Language Models (LLMs) are AI models that businesses can deploy in their own environments. These models can be open-source or proprietary and are customized to meet specific business needs. They can be deployed on various cloud platforms, providing flexibility and scalability for enterprise use. (We listed some sample private LLMs and the platforms for deployment at the end of this article.)

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Detailed Cost Analysis

Usage-Based Costs:

• ChatGPT API: Charges $0.002 per 1,000 tokens. For high-volume operations, such as processing one million tokens a day, this can amount to $2,000 per day or approximately $730,000 per year. This pricing model can become cost-prohibitive for businesses with high or fluctuating usage.
• Private LLM on AWS: Offers more predictable costs. For example, hosting an open-source model like Flan-UL2 on AWS might cost about $150 per 1,000 requests per day and $160 per million requests per day. This predictability aids in effective budgeting and cost management.

Scalability and Long-Term Savings

• ChatGPT API: Initial costs might be low, but they can become expensive as usage grows. The ongoing expenses can quickly add up, making it less cost-effective for large-scale operations
• Private LLM on AWS: While the initial setup may require a higher investment, ongoing operational costs are often lower. For instance, using a fine-tuned LLM with 100,000 sessions per month might cost around $1,400 to $1,500 per month. These costs are more manageable and predictable over time, making private deployments a more economical solution for long-term and large-scale use

Cost Predictability

• ChatGPT API: Costs can be variable and difficult to predict, making budgeting challenging
• Private LLM on AWS: Offers more predictable and controlled costs, facilitating easier budgeting and financial planning. Businesses can forecast their AI-related expenses more accurately, reducing the risk of budget overruns and financial surprises

Conclusion

Deploying private large language models on AWS offers significant cost advantages over using open-source APIs like ChatGPT. The predictable and manageable costs make private deployments a more economical choice for businesses looking to optimize their AI investments. With tailored solutions, operational efficiency, scalability, and long-term savings, private LLMs provide a compelling case for businesses aiming to harness AI for growth and innovation.

More Information

Examples of Private LLMs:

• LLaMA: Meta's LLaMA offers 7B, 13B, and 65B parameter models that can be fine-tuned for specific tasks.
• GPT-NeoX: An open-source model developed by EleutherAI, which can be customized for various applications.
• BERT: Developed by Google, BERT (Bidirectional Encoder Representations from Transformers) is widely used for NLP tasks and can be fine-tuned for specific industries.

Sample Cloud Platforms for Deployment:

• Amazon Web Services (AWS): Offers services like SageMaker for training and deploying LLMs.
• Microsoft Azure: Provides robust AI infrastructure, including Azure Machine Learning for deploying custom models.
• Google Cloud: Offers TensorFlow and other AI services for training and deploying large models.
• IBM Cloud: Provides Watson for AI applications, suitable for deploying custom-trained models.
• Oracle Cloud: Offers AI and machine learning services for deploying private LLMs.

Reference:

• LLM Price Performance
• The ultimate pricing cheat sheet for LLMs
• Chatgpt vs opensource

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Contact us for a free consultation on customized AI solutions! Our experts are ready to help you optimize your operations and enhance innovation using AI technologies.