AI generator statistics: what are the top ones?

2023 © Wikiask
Main topic: Tech
Short answer:
  • 10M+ active users
  • Billions raised in fundraising
  • Up to 540B in parameters

AI generators have significantly grown in popularity in 2022. They are used by millions of users around the world, mostly to help them generative text and visual art. We collect some of the key generative AI statistics in this answer.

Infographic with top generative AI statistics[edit]

Infographic of Generative AI statistics. Generated with Canva and available under CC-BY SA.[1]

Usage: 10M+ users[edit]

  • 10 million users using Stable Diffusion as their AI art generator.[2]
  • 2 million images created per day using DALL-E.[3]
  • 1.5 million users using DALL-E for generative AI art.[3]
Illustration of 2 million images created per day using DALL-E. Generated with DALL-E.

Fundraising: 1B+ invested in generative AI[edit]

  • $1 billion raised by OpenAI, the creator of DALL-E.[4]
  • $125 million raised by Jasper, which leverages OpenAI's GPT-3 AI writer to write content for marketers.[5]
  • $101 million raised by Stability AI, the developer of Stable Diffusion, which is open source.[6]

Valuations: Up to an estimated $20B[edit]

  • $20 billion estimated valuation for OpenAI.[4]
  • $1.5 billion valuation for Jasper.[5]
  • $1 billion valuation for Stability AI.[6]

Parameters used: hundreds of billions[edit]

  • 540 billion parameters used for Google's Pathways Language Model (PaLM), announced on 4 April 2022. Google claimed that this AI was better than all other AIs (including Gopher), but did not release a product.[7]
  • 530 billion parameters used for NVIDIA's Megatron-Turing natural language generation model.[8]
  • 280 billion parameters used for Google's Deepmind's Gopher, announced on 8 December 2021. At the time, Deepmind claimed that this model was better than GPT-3 and other models at language capabilities in all areas analyzed (humanities, social sciences, medicine, general knowledge, science/technology, and maths).[9]
  • 175 billion parameters used for OpenAI's GPT-3, released on 11 June 2020.[10]
  • GPT-4 is expected to have more than 175 billion parameters, but less than the 540 billion parameters of PaLM.[11]
  • 12 billion parameters used for OpenAI's DALL-E, released on 20 July 2022.[12]
  • 5.6 billion parameters used for Stability AI, which leveraged the open-source database LAION 5B, which houses 5.6 billion images from the internet.[13] According to CEO Mohammed Emad Mostaque, the company used 256 NVIDIA A100 Tensor Core GPUs for 150,000 hours in total, at a cost of $600,000.[14][15]


Productivity improvements[edit]

  • 23% to 30% of Github Copilot's shown suggestions were accepted by developers, according to a survey done with 2,000 U.S.-based programmers in 2012.[16]


  1. "Canva: Generative AI infographic".
  2. "Stability AI raises $10m as Stable Diffusion reaches 10m users - Music Ally". Retrieved 2022-11-04.
  3. 3.0 3.1 "DALL·E Now Available Without Waitlist". OpenAI. 2022-09-28. Retrieved 2022-11-04.
  4. 4.0 4.1 "OpenAI, Valued at Nearly $20 Billion, in Advanced Talks with Microsoft For More Funding". The Information. Retrieved 2022-11-04.
  5. 5.0 5.1 Wiggers, Kyle (2022-10-18). "AI content platform Jasper raises $125M at a $1.5B valuation". TechCrunch. Retrieved 2022-11-04.
  6. 6.0 6.1 Wiggers, Kyle (2022-10-17). "Stability AI, the startup behind Stable Diffusion, raises $101M". TechCrunch. Retrieved 2022-11-04.
  7. "Pathways Language Model (PaLM): Scaling to 540 Billion Parameters for Breakthrough Performance – Google AI Blog". Retrieved 2022-11-05.
  8. "Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, the World's Largest and Most Powerful Generative Language Model". NVIDIA Technical Blog. 2021-10-11. Retrieved 2022-11-05.
  9. "Language modelling at scale: Gopher, ethical considerations, and retrieval". Retrieved 2022-11-05.
  10. "OpenAI GPT-3: Everything You Need to Know". Springboard Blog. 2021-11-01. Retrieved 2022-11-05.
  11. Romero, Alberto (2022-06-13). "GPT-4 Is Coming Soon. Here's What We Know About It". Medium. Retrieved 2022-11-05.
  12. "DALL·E: Creating Images from Text". OpenAI. 2021-01-05. Retrieved 2022-11-05.
  13. Wiggers, Kyle (2022-08-12). "A startup wants to democratize the tech behind DALL-E 2, consequences be damned". TechCrunch. Retrieved 2022-11-05.
  14. Retrieved 2022-11-05. Missing or empty |title= (help)
  15. Cai, Kenrick. "Startup Behind AI Image Generator Stable Diffusion Is In Talks To Raise At A Valuation Up To $1 Billion". Forbes. Retrieved 2022-11-05.
  16. Ziegler, Albert (2022-07-14). "Research: How GitHub Copilot helps improve developer productivity". The GitHub Blog. Retrieved 2022-11-05.