公司年报点评科大讯飞

Investment Rating - The report maintains an "Outperform" rating for the company with a target price of 60.68 RMB per share, reflecting a potential upside from the current price of 47.47 RMB [1][8]. Core Insights - The company's revenue is steadily growing, with a notable performance in recurring net profit attributable to shareholders (NPAtS), which surged nearly 60% in 2024. The education business has rebounded with over 20% growth after a decline in 2023, while smart automotive and open platform businesses have also shown strong performance. The continuous upgrades of the company's foundation models are expected to further solidify its leadership in the AI sector [1][8]. Financial Summary - In 2024, the company achieved a revenue of 23.34 billion RMB, representing an 18.79% year-over-year increase. The net profit attributable to shareholders was 560 million RMB, down 14.78% year-over-year, while the recurring NPAtS reached 188 million RMB, up 59.36% year-over-year. For Q1 2025, revenue was 4.66 billion RMB, up 27.74% year-over-year, with a net profit attributable to shareholders of -193 million RMB [3][8]. Revenue Forecast - Revenue forecasts for 2025 and 2026 are set at 28.06 billion RMB and 33.80 billion RMB, respectively, with an additional forecast for 2027 at 41.03 billion RMB. The company is expected to maintain a strong revenue growth rate despite its substantial revenue base [1][8]. Business Performance - The company's various business segments, including smart education, open platform, smart city, consumer, smart automotive, operator, and smart healthcare, reported revenues of 7.23 billion RMB, 5.17 billion RMB, 3.62 billion RMB, 2.71 billion RMB, 0.99 billion RMB, 1.90 billion RMB, and 0.69 billion RMB, respectively, with year-over-year changes of +29.94%, +31.33%, -8.1%, +20.8%, +42.16%, -9.31%, and +28.18% [3][8]. AI Model Development - The Spark foundation model has become a crucial growth driver for the company, leading in project awards in 2024. The model was upgraded on April 21, matching the performance of industry leaders like OpenAI and DeepSeek while maintaining a smaller parameter size [1][8].