Pre-IPO stock tokens, on an order book
There is no exchange for OpenAI stock.
An automated market maker quotes against a price formed somewhere else. For these companies there is nowhere else. TornaCurb is where the price gets made — a real order book for shares that never had a venue.
Never used an order book? Three minutes, no wallet needed →
Live on devnet · test tokens, not shares · real SPL escrow, no indexer · external audit pending · notice
Before a company was listed on the New York Stock Exchange, its shares traded on the curb — literally on the sidewalk outside the exchange. The Curb Market existed for one reason: there were shares people wanted to trade, and no exchange willing to list them. That gap is open again.
A curve has to guess. A book already knows.
An automated market maker quotes off a formula anchored to a reference price. For a private company there is no reference price to anchor to, and the float is thin, so the curve is steep exactly where it matters. A book quotes where makers are actually willing to trade.
Modelled, not measured: no such pool exists for a pre-IPO name. Half the stated TVL in each leg, priced at the book's best ask.
The gap is not a trick of the numbers — it is the instrument. A pool must hold inventory across every price at once, so thin liquidity means a steep curve. A maker on a book commits capital only at the price they chose, which is why order books work in markets that are too thin to support a pool at all.
Ten listings, two kinds
The split is the argument. For most of these private companies nothing publishes a price at all; Pyth does index OpenAI and Anthropic, but an index reports discovery happening on secondary venues rather than performing it, and it gives you no limit order and no price-time priority. The listed pair is a control group: where a price is formed on a real exchange, you can watch how closely the book tracks it — and only then is it reasonable to trust the same machinery where no exchange exists at all.
Real limit orders
“Buy at 180 or better” is the most basic instruction in equities. A curve cannot express it; a book is made of them.
Price-time priority
The maker who quotes first and tightest gets filled first. That is what makes anyone quote tight.
Makers keep their edge
A pool cannot move its quote when the world reprices, so it gets picked off. A maker cancels and re-quotes.
None of this works if the book cannot take concurrent quotes. TornaCurb runs on Torna, our own open-source index, which is what makes that possible on Solana.
Why the writes run in parallel
The usual on-chain book keeps each side in one slab account, so every order on a side takes the same write lock and serializes, one per slot. Torna puts each B+ tree node in its own account, so orders that fall in different leaves touch different accounts and Solana commits them in the same slot. A deep book spreads its price levels across many leaves.
land in different leaves vs. one shared leaf
Measured on a single-node solana-test-validator, the real Agave banking stage, via torna/bench (./run.sh reproduces it; method and data). Devnet is shared and noisy, so the controlled number is the honest one. This parallelizes book maintenance, not matching: top-of-book is price-time serial by definition, and nothing can change that.