Meitu's Q1 2026 Core Revenue Up 34%, Meets Expectations; AI Monetization Emerges as New Engine

Overview

This report provides UBS's analysis of Meitu Inc.'s Q1 2026 business update. It notes that Meitu's core imaging, video, and design product revenue reached RMB 852 million in Q1 2026, up 34.3% YoY, broadly matching UBS's earlier full-year 38% growth forecast. The report particularly highlights the accelerating contribution of AI features to user monetization, positioning them as a new growth driver. Based on this, UBS reaffirms its 'Buy' rating and a 12-month target price of HK$8.40.

Core views

Core revenue growth meets expectations: In Q1 2026, Meitu's core imaging, video, and design products generated RMB 852 million, up 34.3% YoY. Casual app revenue stood at RMB 699 million, up 35.5% YoY, accounting for 82% of core revenue; productivity app revenue totaled RMB 153 million, up 45.4% YoY, representing 18% of core revenue. Overall, core revenue growth closely aligns with UBS's full-year 38% projection. Paid user growth shows structural differentiation: Casual app paid users reached 15.56 million, up 27.4% YoY—slightly below the full-year forecast—while productivity app paid users hit 2.34 million, up 52.9% YoY—exceeding the annual target. This indicates rapid penetration of productivity apps. AI monetization emerges as a new growth engine: As of March 2026, Meitu's AI-driven productivity apps generated an ARR of RMB 580 million, up 56.2% YoY—3.78 times the productivity app revenue from Q1 2025. Additionally, AI credits consumed by users in March increased by 59% compared to December 2025. UBS believes these trends demonstrate that AI-powered features or intelligent agents are increasingly driving Meitu's user monetization.

Analysis framework

The analytical framework of this report is clear: starting from the company's voluntarily disclosed quarterly business data, it compares actual growth rates against UBS's previously established full-year forecast model. Through volume–price decomposition, analysts separately examine two key dimensions—user scale and monetization capacity—to assess the sustainability of growth. On the user side, the report breaks down paid user counts and net additions across casual and productivity segments; on the monetization side, it introduces ARR (Annual Recurring Revenue) and AI credit consumption as forward-looking indicators. This analytical path—from user growth to revenue expansion, then further down to specific AI consumption metrics—strongly supports the central conclusion of 'accelerating AI monetization,' thereby validating both the 'Buy' rating and the target price.

Methodology notes

• Industry/Segment Analysis FrameworkVolume-price decomposition

  Volume–Price Decomposition Analysis

  The report splits revenue growth into two components—paid user count (volume) and ARPU/paid amount (price)—and validates each separately across casual and productivity business segments, helping readers discern whether growth stems from expanding user base or increasing per-user spending.

• Event Game Theory and Behavioral FinanceExpectation Gap/Expectation Management

  Comparative Validation of Actual Data vs. Full-Year Forecasts

  The report contrasts Q1 2026's actual growth rate with analysts' prior full-year projections—for example, casual app paid user growth lagging behind expectations while productivity outpaced them—enabling readers to gauge the likelihood of achieving annual targets through quarterly tracking.

• Valuation Methodology

  ARR (Annual Recurring Revenue) as a Forward-Looking Metric

  ARR is commonly used to evaluate the scale and stability of SaaS or subscription-based software businesses. The report incorporates ARR as a forward-looking valuation reference and calculates its multiple relative to current-quarter productivity revenue, assessing the visibility of future AI-related income and the pace of monetization acceleration.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Meitu Inc. (1357.HK)

  The report directly covers the subject, benefiting from steady core revenue growth and accelerated AI monetization.

  Strengths

  Stable growth in the core imaging and design business; significant ARR growth in AI-driven productivity apps, accompanied by surging AI credit consumption, highlighting strong AI monetization potential.

  Risks

  Slower-than-expected globalization; competitive pressure from major players or other AI startups launching more advanced products; declining inference costs for large models intensifying competition.

Key data

• Q1 2026 Core Imaging, Video, and Design RevenueRMB 852 millionUp 34.3% YoY, in line with UBS's full-year 38% growth expectation
• Q1 2026 Casual App RevenueRMB 699 millionUp 35.5% YoY, accounting for 82% of core revenue
• Q1 2026 Productivity App RevenueRMB 153 millionUp 45.4% YoY, accounting for 18% of core revenue
• Q1 2026 Casual App Paid Users15.56 millionUp 27.4% YoY, slightly below full-year expectations
• Q1 2026 Productivity App Paid Users2.34 millionUp 52.9% YoY, exceeding full-year expectations
• AI-Driven Productivity App ARR (as of March 2026)RMB 580 millionUp 56.2% YoY, 3.78 times the productivity app revenue from Q1 2025
• March AI Credit Consumption Increase Compared to December 2025Up 59%Compared to December 2025, indicating rapidly rising usage frequency of AI features

Impact & implications

The report concludes that Meitu's current performance validates the sustainability of its core revenue growth, particularly as AI feature penetration substantially enhances user monetization efficiency. Quantitative analysis also suggests potential improvements in industry structure, with the possibility of EPS exceeding expectations in the next earnings report—driven primarily by faster-than-expected growth in paid users. This reflects growing market recognition of Meitu's AI monetization strategy.

Risks

• Upside Risks: Faster-than-expected globalization; breakthroughs in DesignKit capabilities accelerating paid user growth; self-developed GenAI model MiracleVision evolving faster than anticipated using user data.
• Downside Risks: Slower-than-expected globalization; introduction of more competitive products by large cloud providers or other AI startups; reduced inference costs for large models leading to intensified competition.

What to watch

• Trends in subsequent AI credit consumption growth and its substantial impact on ARPU.
• Whether productivity app paid user growth can sustainably exceed full-year expectations.
• Whether casual app paid user growth can rebound to meet full-year forecasts.