Lattice Semiconductor posted second quarter 2025 revenue of $124 million, essentially flat year-over-year, with GAAP net income dropping 87% to $2.9 million, or $0.02 per diluted share. On a non-GAAP basis, earnings per share were $0.24, up from $0.23 a year ago, with adjusted EBITDA margin improving to 34.1%. Operating cash flow rose sharply to $38.5 million, representing a 31.1% margin. Free cash flow reached $31.3 million, up from $14.8 million in the prior year.
The company highlighted broad-based growth, normalized channel inventory, and momentum from record design wins in cloud datacenter, wired communications, industrial robotics, ADAS, and edge AI. Automotive and industrial markets showed recovery trends. However, GAAP operating income fell to $4.7 million from $22.6 million a year earlier, pressured by higher R&D and SG&A expenses.
Looking ahead, Lattice forecast third quarter revenue between $128 million and $138 million, with non-GAAP EPS of $0.26 to $0.30. Gross margin is expected around 69.5% (±1%), with operating expenses of $52–$54 million. The company also underscored new partnerships, expanded FPGA product launches, and increased stock buybacks.
• Q2 2025 revenue: $124 million; GAAP EPS: $0.02; non-GAAP EPS: $0.24
• Adjusted EBITDA margin: 34.1%; free cash flow margin: 25.2%
• GAAP net income down 87% year-over-year; non-GAAP net income up 3.7%
• New FPGA launches: Certus-NX and MachXO5-NX targeting AI, automotive, and industrial markets
• Collaboration with Mitsubishi Electric on next-gen factory automation
• $71 million in stock repurchases through H1 2025
• Q3 2025 revenue guidance: $128–$138 million; non-GAAP EPS: $0.26–$0.30
“We delivered another strong quarter, with broad-based growth across key financial metrics and record design wins,” said Ford Tamer, CEO of Lattice Semiconductor.
🌐 Why it Matters: FPGA demand is rising as AI workloads move to the far edge, driving growth opportunities for low-power programmable solutions. Lattice’s positioning in communications, industrial automation, and automotive markets underscores the shift toward highly specialized silicon in AI infrastructure.
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