Cohu's Q4 2024: Navigating Contradictions in Mobile Recovery, Margins, and Market Timing

These are the key contradictions discussed in Cohu's latest 2024 Q4 earnings call, specifically including: Mobile Segment Recovery Expectations, Gross Margin Expectations, Automotive and Industrial Segment Utilization, Market Recovery Timing, HBM Opportunity Expansion, Software Revenue Growth Expectations, and Mobile Segment Recovery Timeline:



Revenue and Order Delays:
- Cohu reported revenue of $94.1 million for Q4 2024, within guidance, with recurring revenue representing 62% of total revenue.
- Guidance for Q1 2025 revenue was adjusted to approximately $97 million due to recent customer requests to delay Q1 shipments.
- These delays were attributed to ongoing inventory corrections and customer-specific market conditions.

Gross Margin Challenges and Inventories:
- Q4 gross margin was 41.8%, affected by a $2.1 million charge related to inventory reserves for old, slow-moving, customer-specific inventory.
- The company recorded a 45% non-GAAP gross margin for the full year 2024, higher than modeled due to strong recurring revenue.
- The challenges in gross margin were due to inventory adjustments and market dynamics, particularly in automotive and mobile segments.

Expansion into New Markets:
- Cohu entered the high-bandwidth memory (HBM) and silicon carbide markets, with orders and revenue expected from these segments.
- Estimated HBM-related revenue for 2025 is $7 million, with potential to support HBM3 and new HBM4 product ramp later in the year.
- The expansion is focused on data center and edge AI applications, aligning with Cohu's strategy to capitalize on growth opportunities in these areas.

Software and AI Initiatives:
- The acquisition of Tignis, a software provider, is expected to contribute to Cohu's growth, with a projected annual growth rate of 50% or more over the next 3 years.
- Cohu qualified its DI-Core software and received orders to optimize visual inspection yield for a major semiconductor manufacturer.
- These initiatives are aimed at leveraging AI to optimize yield and productivity, addressing the growing demand for advanced semiconductor manufacturing tools.