129 China’s leading sportswear companies, Anta Sports and Li-Ning, are reportedly exploring a joint bid to acquire German brand Puma, according to sources cited by Reuters. The potential move marks a significant escalation in global sportswear consolidation — and a bold play by Chinese firms to expand their international footprint. French luxury group Kering holds a 1.5% stake in Puma, having previously spun it off in 2018. While talks are still in preliminary stages and no formal offer has been made, insiders suggest the two Chinese companies are assessing the feasibility of a deal that could reshape the global athletic apparel landscape. Anta, known for acquiring Finland’s Amer Sports (which owns Salomon and Wilson), and Li-Ning, a homegrown sportswear leader in China, would bring complementary strengths to the table. A successful acquisition would give them access to Puma’s strong distribution in Europe, global brand equity, and heritage in performance wear. The move comes at a time when both companies are seeking growth beyond a saturated Chinese market, and as Chinese capital looks outward for expansion opportunities. A Puma acquisition would allow them to diversify their portfolios and position themselves as credible challengers to Nike, Adidas, and emerging American DTC brands. It also reflects the increasing ambition of Chinese consumer brands to go global — not just through exports or sponsorships, but via ownership of legacy international brands. For Puma, the bid signals rising valuation interest amid a rebound in consumer demand and category growth. You Might Be Interested In Revolutionizing Retail: Skechers Introduces AI-Powered Luna in Singapore LinkedIn expands video ads with brandlink & pushes creator-led content Merit Beauty Defies Beauty’s Fast Lane with a Slow-Burn Marketing Strategy Sundar Pichai says AI could even take over his job — “CEO could be automated” Marc Benioff backs Gemini 3, says he’s “done with ChatGPT” Google Marketing Platform Launches “AI Insights Hub” for Smarter Cross-Channel Optimization