Invest1 publisher3 min readPublished Updated
Unitree prices at 35 times sales, and humanoid robotics finally has a public comparable
A roughly $9bn valuation on $253m of revenue, actual profits and 5,500 humanoids shipped. The 8,000x retail oversubscription hints at what buyers will actually pay.
The Investor · Invest desk
Drafted by a language model from the sources cited here and checked against its claim ledger before publication. How we use AISend a correction
What happened
- Unitree priced shares for its Shanghai STAR Market IPO at 150.80 yuan each, about $22.37, implying a company valuation of roughly $9 billion.
- Trading is expected to start between August 17 and August 21.
- The retail portion of the deal drew extraordinary demand, with oversubscription reported near 8,000 times.
- Unitree was founded in Hangzhou in 2016 and develops quadruped and humanoid robots aimed at research, industrial and consumer markets.
- Unitree posted revenue of approximately $253 million in the most recent year, a 335 percent rise.
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Why it matters
Unitree has priced its Shanghai STAR Market offering at 150.80 yuan a share, about $22.37, implying a valuation of roughly $9bn [1]. That matters because it is one of the first pure-play humanoid robotics companies to reach public markets on the Chinese mainland [13], which means the sector now has a printed multiple instead of a private-round narrative.
The underlying business is unusually legible for this category. Unitree, founded in Hangzhou in 2016 and selling quadruped and humanoid robots into research, industrial and consumer channels [5], posted revenue of about $253m in its most recent year, up 335% [6]. That implies a prior-year base of roughly $58m [2]. It delivered more than 5,500 humanoid units [7], and it has reached profitability, which most of its peers have not [8]. Proceeds are earmarked for robot models, hardware, new products and more production capacity [9].
So the anchor number is about 35.6 times trailing revenue at the offer price [1]. For a hardware-heavy business compounding at 4.35x year over year and actually earning money, that is the figure every private humanoid round will now be marked against, whether founders like it or not. A cruder sanity check: $253m across 5,500 humanoids is about $46,000 per unit [3], and since that revenue also includes quadrupeds, true humanoid average selling price is below that. This is still a machine-shop economics story, not a software one.
The demand signal says 35x is not the clearing price. The retail portion drew oversubscription reported near 8,000 times [4], and trading is expected to begin between August 17 and August 21 [3]. Offshore, pre-IPO perpetual futures on Hyperliquid have traded between $92 and $94 a share [10], which the report puts at an implied valuation near $38bn and more than fourfold upside from the offer [11]. That is 4.11x to 4.20x the IPO price [5] and roughly 150 times revenue [4]. Traders there are said to be pricing Chinese retail enthusiasm, the limited float created by the deal structure, and general optimism about embodied AI [14].
Treat that $38bn print with care. The two Hyperliquid markets carry open interest of about $9.1m on turnover near $59m [12], meaning open interest is roughly 0.10% of the IPO valuation being repriced [6] and turnover is about 6.5 times open interest [7]. That is a fast, thin, mostly speculative venue, not a book with size. Crowdfund Insider notes that prior pre-listing contracts have tracked actual opening prices reasonably closely in some cases [15], and also that an opening only double the offer price could still pressure a significant share of long exposure [16]. Secondary markets outside China have shown premiums too, though less extreme [17].
Watch the first session and then the gap between the synthetic contracts and the cash price [15][11]. Watch the float: scarcity explains a chunk of any opening pop, and it unwinds. And watch the second year of growth, because as the report itself concedes, richer valuations require sustained growth against competitive pressure and the practical difficulty of scaling complex hardware and software together [18].