DeepSeek Says 1.54 Million People Use Its Agent Software Daily
The company also reports about 92 trillion tokens of daily use through its official API. The figures suggest rapid adoption of Harness, but measure different things and remain independently unchecked.
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Nov 9, 12:00 UTC ·
782 words
Follows "Everything is a Plugin": DeepSeek Hands Tasks to Codex and Claude Code.
DeepSeek says its Harness agent framework reached 1.54 million daily active users in less than three months, putting a large adoption claim behind its push into AI agents. [1]
An AI agent is a system that uses tools and works through steps to carry out a task, rather than simply answering a question. Harness supplies the software connections and workflow that make that possible. [1]
Users connecting Harness through DeepSeek's official API consumed about 92 trillion tokens a day as of November 4, 2026, according to company figures reported by the South China Morning Post on November 9. That is roughly 1.1 billion tokens a second. [1]
Neither figure has been independently verified. DeepSeek's definition of a daily active user, including whether it counts only API users and how it separates people from automated activity, is not clear. The period and counting method behind the daily token total have not been established either. [1]
Harness's adoption is a different measure from the audience for DeepSeek's chatbot or the quality of a particular model. The competitive prize is becoming the software developers use to put models to work. [1][2]
The software around the model
DeepSeek describes the framework's organising idea in its repository with a short line: "Everything is a Plugin." The company has released Harness as open-source software under the MIT licence. [2]
A model generates responses. A harness supplies the connections and manages the workflow that allow the system to take further steps, using tools rather than stopping after an answer. That surrounding software is what turns a model into part of an agent system. [1]
The distinction matters when judging the user figure. Someone using Harness is using infrastructure for working with a model, not necessarily DeepSeek's consumer chatbot. [1][2]
The plugin design makes those connections central to the product. Instead of presenting Harness as a single model with a fixed set of abilities, DeepSeek describes a framework built from components that can be plugged into it. [2]
For a developer, that separates two choices: which model supplies the responses and which software organises the work. A framework can be valuable because of how it connects the parts, even without being a new model itself. That is why a framework's adoption deserves attention alongside model releases.
That puts the company into a contest over how developers assemble AI applications. In the rivalry between China's DeepSeek and US companies such as OpenAI and Anthropic, agent frameworks offer another way to attract developers alongside releasing models. The software that coordinates work can matter even when the underlying model changes. [1]
Open-source distribution also gives developers a different relationship with the product from simply using a hosted chatbot. They can inspect and adapt the code.
The MIT licence broadly permits reuse and modification, including in commercial software, subject to its terms. DeepSeek has chosen that permissive route for Harness. [2]
What 92 trillion tokens measures
The token figure has a narrower stated scope than the daily-user figure: it concerns Harness users connecting through DeepSeek's official API, the interface through which software accesses its hosted models. [1]
Tokens are the pieces of text a model processes or produces. They measure activity, not finished jobs or paying customers. A long exchange, repeated attempts at a task and a short successful request can produce very different token totals.
The roughly 1.1 billion tokens a second is a way to express the claimed daily volume at a more familiar timescale. Dividing 92 trillion by the 86,400 seconds in a day gives about 1.06 billion, rounded to 1.1 billion. It is an equivalent average rate, not a separate measurement of peak traffic. [1]
Dividing that total by 1.54 million would also give a misleading impression of precision. The token total explicitly covers official API traffic, while the daily-user total has no equally clear boundary. They are not established as matching populations. [1]
There are two different business questions here. Adoption of the framework concerns DeepSeek's reach among people building or using agent systems. Traffic through its hosted API concerns use of a service it operates.
The figures could help assess both, but treating them as interchangeable would blur the difference between distributing software and serving model requests.
A large claim for a preview product
Harness's repository still labels the project a "developer preview" and warns that changes may break compatibility. The reported adoption milestone therefore sits alongside an explicit warning that the software is still changing. [2]
For anyone building on it, that warning has a practical meaning: future changes may require adjustments to their own software. Open access to the code does not remove that maintenance burden.
DeepSeek has put two striking numbers behind its agent strategy. The next useful benchmark is whether it can connect that activity to reliable, completed tasks.
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