Liu Liu Liu Fashion Supply Chain (Hangzhou) Co., Ltd.

Liu Liu Liu Fashion Supply Chain (Hangzhou) Co., Ltd.

1688
TopsBottomsOuterwearShoes
Seller Intelligence

六六六潮牌供应链(杭州)有限公司 – A Quick Look

If you’re hunting for tops on 1688, this supplier’s got your back. They’re a wholesale outfit based in Hangzhou, packing 130 listed products with a heavy focus on Tops – no random accessories or shoes muddying the catalog. The crowd favorite? The Essentials Full Zip Hoodie, which seems to be the clear winner in their saved-and-liked stats.

What They Sell
Strictly tops. No messing around. The entire inventory is geared toward hoodies, tees, and maybe some jackets – but the data only flags “Tops” as the primary category. If you need pants or outerwear, look elsewhere.

Warehouse Delivery Vibe (to Your Agent)
No shipping data was provided here, so I can’t give you a read on how fast they pack and send to your proxy warehouse. You’ll want to ask your agent for a test order or check the supplier’s dispatch history before committing big.

The Good

  • Zero defect records – That’s a clean slate. No reported flaws or return drama in the dataset.
  • Focused inventory – 130 tops means decent variety within one lane. Good for bulk buyers or proxy shoppers looking to consolidate a clothing haul.
  • Top-saved hoodie – The Essentials Full Zip Hoodie is clearly pulling eyes. Could be a solid bet for unbranded streetwear basics.

The Bad (or the Unknown)

  • No recent reviews or rating data to back up the hype. The track record is a blank page, so you’re rolling the dice a bit on quality and customer satisfaction.
  • Limited category scope – if your list includes anything beyond tops, this isn’t a one-stop shop.
  • With only 130 items and no dispatch timeliness info, you might face slower domestic shipping to the agent warehouse. Always clarify lead times before ordering.

Bottom Line
A decent 1688 find if you’re after tops and want a clean defect sheet. But without reviews or shipping metrics, treat it as a test-run candidate – order a sample first, then scale up.

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