The Cost of Using ChatGPT: What You Need to Know
If you’re considering using ChatGPT, it’s important to know that it is not a free service. When you sign up for an account, you will receive a grant of 100,000 tokens, which has a value of $18.00. This grant is valid for three months, or until you use up all of the tokens, whichever comes first.
After you have used up your initial grant, the cost of using ChatGPT will be $0.0200 per 1,000 tokens. This pricing is for the Davinci model, which is the most advanced and expensive option available.
It’s essential to keep track of your token usage and budget accordingly to avoid any surprise charges. If you’re using ChatGPT for a large project or on an ongoing basis, it’s a good idea to factor the cost into your budget upfront.
It cost them lots of money.
OpenAI’s ChatGPT is a popular language model that allows users to communicate with a virtual assistant through natural language. According to a recent analysis, ChatGPT is hosted on Microsoft’s Azure cloud platform.
Minimum of 8 GPUs required for a single ChatGPT query
In terms of cost, Microsoft charges $3 per hour for the use of a single A100 GPU. Each word generated by ChatGPT costs $0.0003, so a single response from the model, which typically contains at least 30 words, costs at least 1 cent.
ChatGPT’s running cost is very high.
Based on these estimates, it is believed that OpenAI is spending around $100,000 per day or $3 million per month on the running costs of ChatGPT. While this may seem like a significant investment, the benefits of using a cloud-based platform like Azure likely outweigh the costs for the company, having in mind that Microsoft is the only significant investor in OpenAI and eventually, they will get the return on investment, especially if they implement it with their Bing search engine.
Not only does hosting ChatGPT on Azure eliminate the need for expensive physical infrastructure, but it also allows for greater scalability and flexibility. This means that OpenAI can quickly and easily increase or decrease its use of the platform based on demand without the need to purchase additional hardware or worry about hardware maintenance and upkeep.