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Trading Infrastructure

Why SyncSwap Runs Four AMM Invariants

SyncSwap’s four pool models match different assets and LP risk appetites, trading a simpler AMM design for sharper routing and integration choices.

Crypto Market Dispatch Newsroom 3 min read
Why SyncSwap Runs Four AMM Invariants

By September 11, 2026, SyncSwap supported four AMM invariants because one curve cannot price uncorrelated tokens, pegged assets and concentrated liquidity with equal efficiency. The architectural change is clear: V1 offered Classic and Stable pools, while the current protocol overview adds Aqua and Range pools behind a shared routing interface.

What are SyncSwap’s four AMM invariants?

They are four pricing regimes designed for different assumptions about asset correlation, trading volume and liquidity-provider involvement. The current overview from Syncswap names the models, although “four invariants” should not be read as four minor variations of one formula.

  • Classic: A constant-product curve, x multiplied by y equals k, provides liquidity across the full price range. It suits volatile or long-tail pairs but spreads capital thinly.
  • Stable: A hybrid curve behaves closer to constant sum around a presumed peg, then shifts toward constant product as reserves become unbalanced. Pegged pairs receive deeper effective liquidity, at the cost of relying on their correlation.
  • Aqua: A dynamic hybrid design based on the two-asset CryptoSwap model automatically concentrates liquidity around an internal price and adjusts fees as balance conditions change.
  • Range: Liquidity providers choose price bands, concentrating capital where they expect trading to occur. Positions stop earning fees when the market leaves their range and may become entirely one-sided.

The router turns model choice into execution

SyncSwap’s predecessor design asked builders to choose between a general-purpose curve and a stable-asset curve. Four models widen that choice: an issuer can seed a pegged market in Stable, a passive LP can use Aqua for automated concentration, and an active market maker can specify bands in Range. The router can compare paths across those pools, so a trader need not select the invariant manually.

That modularity also raises integration costs. Quoting software must understand pool-specific math, fee behavior and liquidity states. A Range position can appear well funded while providing nothing at the current price; an Aqua quote depends on more moving parts than a Classic quote. Builders therefore gain precision but lose the simplicity of assuming every pair follows x multiplied by y equals k.

Who supplies liquidity, takes risk and collects fees?

Users and professional market makers supply the tokens; traders consume that inventory and pay pool-specific swap fees. Liquidity providers bear inventory loss, adverse selection and, for Range pools, the operational risk of choosing or maintaining a useful band. Traders bear price impact and execution risk when routes cross shallow pools.

SyncSwap’s documentation says LPs earn trading fees, while its pool contracts also permit a configured protocol share to accrue through a fee recipient. Aqua supports dynamic fees, whereas Classic and Stable pools can use fixed settings. Because fee management is configurable, a single advertised percentage would not reliably describe every pool or deployment.

Four curves are useful, not automatically liquid

The practical significance is choice at the market-design layer. SyncSwap can match capital to a pair’s behavior without forcing every LP into manual range management, a meaningful advantage over a single-invariant exchange. But adding invariants does not create volume, improve token quality or guarantee that routing will find deep liquidity.

The defensible verdict is that four models make SyncSwap a more capable venue for builders, provided integrations treat each pool as a distinct risk system. What remains unknown from the model descriptions alone is how liquidity is distributed among them, which models are active on every supported network, and whether Aqua’s automation outperforms actively managed Range positions after fees and rebalancing losses.

Topics in this dispatch

  • Trading Infrastructure
  • Protocol Economics

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