Manus reaches $100m ARR eight months after launch

Manus, an AI agent startup with offices in Singapore, Tokyo, and San Francisco, said it has reached an annual recurring revenue (ARR) of over US$100 million just eight months after launch.

The company also reported a revenue run rate exceeding US$125 million, which includes usage-based and other revenue streams.

Manus claimed it has processed more than 147 trillion tokens and created over 80 million virtual computers since its launch.

Earlier this year, the company introduced what it described as the first general AI agent.

Manus raised US$75 million prior to launch in a round led by Benchmark, whose general partner Chetan Puttagunta joined the board.

The company employs 105 people and plans to open a Paris office.

🔗 Source: Manus

🧠 Food for thought

Implications, context, and why it matters.

Manus’s $100M ARR and $125M run-rate are different metrics

Manus lists “$100M ARR” and a “$125M revenue run rate” that folds in usage-based and other streams 1. ARR usually equals monthly recurring revenue times 12 without usage-based or one-time payments 2.
Over 80 million virtual computers created since launch 1 signal heavy compute work. The company has not shared gross margins or infrastructure costs tied to E2B (a sandboxing provider whose platform runs workloads in Firecracker micro virtual machines, lightweight VMs used to isolate compute tasks) 3, so unit economics remain unclear.
Third-party web traffic estimates flag a slide 4. Visits fell from 23.76 million in March 2025 to 17.3 million in June, which puts retention in doubt.

Enterprise software vendors can target Manus’s customer base with cost optimization and governance tools

Manus processed 147 trillion tokens 5 across models it leans on, including Anthropic’s Claude 3.5/3.7 Sonnet and Alibaba’s Qwen (Alibaba’s family of large language models) 6. That spend invites vendors selling cost tracking, usage analytics, and multi-model controls for agent-heavy teams.
E2B’s sandbox setup 3 and multi-agent architectures that execute code autonomously (systems where multiple AI agents coordinate to plan and run code with minimal human oversight) 6 create security and compliance gaps. IT vendors can build observability tools, audit logging, or compliance frameworks for production agentic systems.
B2B SaaS teams can find Manus adopters in the use case gallery on its site 7 for outreach to sell workflow integrations, data connectors, or security overlays.