Online storage expands to support over 1 billion ChatGPT users
openai
| Source: OpenAI | Original article
OpenAI has turned its Habitat Python library into a globally distributed storage platform that now serves over 1 billion ChatGPT users and handles 22 million requests per second.
OpenAI has unveiled that its internal storage system, Habitat, has been upgraded from a modest Python library into a globally distributed platform capable of handling the data needs of more than one billion ChatGPT users. The revamped infrastructure now processes roughly 22 million storage requests per second, a scale the company disclosed in a technical blog post on September 11, 2026.
Habitat underpins not only ChatGPT but also other OpenAI services such as Codex, providing a unified backend for user prompts, model outputs and session state. By spreading data across multiple data‑center regions, OpenAI aims to keep latency low and reliability high even as its weekly active user base swells beyond the 250 million mark reported earlier this year. The move signals that the firm is moving beyond the “research‑grade” tooling that once powered its models and is now investing in production‑grade storage that can sustain billion‑scale traffic.
The upgrade matters because storage latency and availability are becoming the bottlenecks for conversational AI at massive scale. A robust, low‑latency backend enables faster response times, more complex multi‑turn interactions and the possibility of richer, personalized features without compromising user experience. It also demonstrates OpenAI’s confidence in its infrastructure roadmap, a factor that could influence enterprise adoption and competitive dynamics in the AI‑as‑a‑service market.
Going forward, observers will watch how OpenAI balances the cost of such a high‑throughput system with pricing for end users, whether Habitat’s architecture will be opened to external developers, and how the platform copes with future spikes in demand as the company pushes toward a full‑billion‑user milestone. Further technical details or performance benchmarks are likely to follow in upcoming OpenAI releases.
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