344
Productivity & Workflow355
Automation & Workflow225
Software Development251
Marketing & Growth192
AI Infrastructure & MLOps175
Writing & Content Creation203
Data & Analytics142
Photography & Imaging156
Design & Creative170
Customer Support132
Sales & Outreach125
Voice & Speech135
Education & Learning131
Operations & Admin87
Moonshot AI, maker of Kimi K3, is targeting $2 billion in annualized revenue by the end of 2026, according to Bloomberg and reported by TechCrunch.
In short: Moonshot AI says it is aiming to reach $2 billion in annualized revenue by the end of 2026.
Moonshot AI, a well-known AI lab in China and the maker of the Kimi K3 model, is targeting $2 billion in annualized revenue by the end of this year. This was reported by Bloomberg and covered by TechCrunch.
“Annualized revenue” is a way to estimate yearly sales based on recent results (like taking one month’s pace and multiplying it across a year). Bloomberg said this target would be about double Moonshot’s reported revenue pace in August.
The goal is tied to the company’s K3 model, which was released this summer. TechCrunch noted that K3 usage has dipped a bit in recent months, but OpenRouter data still shows heavy activity, with as many as 300 billion “tokens” generated each day. Tokens are small chunks of text that AI models read and write (like counting words, but in smaller pieces).
Moonshot’s revenue target is still far below some rivals. Recent reports put OpenAI at about $40 billion in annualized revenue and Anthropic at about $65 billion.
Moonshot also faces controversy. Anthropic recently accused Moonshot of “model distillation,” which is when one AI system is trained by copying another system’s answers (like using someone else’s solved homework to learn the patterns). Anthropic alleged that large numbers of requests were routed to its Claude Opus model and that more than 23 million responses were collected for training.
This story highlights two things at once, the push to make real money from AI products and the growing disputes over how AI companies get the data and examples they use to train their systems.
Source: TechCrunch AI