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SLAB earnings

Silicon Laboratories — automated research on every print, the model's read of every earnings call, and the numbers against estimates.

Next report November 03, 2026 consensus EPS 0.82
§ Recent prints / EPS vs consensus
Reported EPS Consensus Surprise
Aug 11, 2026 0.71 0.69 +2.9%
May 05, 2026 0.53 0.49 +8.2%
Feb 04, 2026 0.56 0.54 +3.7%
Nov 04, 2025 0.32 0.30 +6.7%
§ Research / every print, covered
SLAB Q2 FY2026 earnings: EPS beat by 2.9%, revenue in line
Power & Analog Desk · RegardingSemi Engine · Aug 11, 2026

Silicon Laboratories reported Q2 FY2026. EPS came in at $0.71 against a $0.69 consensus, beat by 2.9%. Revenue was $228.2M versus $228.0M expected, in line. Gross margin was 64.3%, up 760 bps from last quarter.

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Silicon Labs’ miss is the wrong signal: margin and channel math say the recovery is cleaner than the revenue headline
Power & Analog Desk · RegardingSemi Engine · Nov 04, 2025

Silicon Laboratories missed Street revenue by -2.8%, but the actionable surprise was that EPS beat by +6.7% while channel days and gross margin both moved in the direction needed for a durable recovery. The market may be mispricing this as a demand-quality problem when the print instead shows a controlled rebuild: revenue is back above $206.0 million, non-GAAP EPS beat the guide midpoint by $0.02, and December guidance embeds sequential growth with a stabilized margin framework near 61%.

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Silicon Labs’ miss is the wrong fight: the turn is in mix, channel refill, and operating leverage
Power & Analog Desk · RegardingSemi Engine · Aug 05, 2025

Silicon Laboratories missed the Street’s revenue number by -5.7%, but the actionable signal is that EPS beat by +22.2% while management guided September revenue to $200 million to $210 million and gross margin to 57% to 58%. The market may be overpricing the top-line miss and underpricing a cleaner recovery in industrial, distribution sell-through, and margin, with the risk that the recovery remains too channel-dependent rather than demand-led.

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§ Earnings calls on file / full text, model-annotated
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