Best AMM Protocols: A Comparative Guide

The leading automated market maker (AMM) designs differ primarily in the mathematical formula they use to price trades, which in turn determines whether they're better suited for volatile asset pairs, closely correlated stable assets, or highly customized multi-asset portfolios.

Why AMM design isn't one-size-fits-all

Every AMM replaces a traditional order book with a mathematical formula that automatically prices trades against pooled liquidity, as covered in our broader DEX vs. CEX explainer. But the specific formula chosen has real consequences: a formula tuned for two volatile, uncorrelated assets behaves very differently from one tuned for two stablecoins that should always trade near the same value.

Constant-product AMMs

The original and still most widely used design prices trades so that the product of the two pooled assets' quantities stays constant. It works reasonably well for any pair, requires no special assumptions about the assets' relationship, and is simple to reason about — but it spreads liquidity thinly across the entire price curve, meaning much of the pool's capital sits at prices that will rarely, if ever, be reached.

Concentrated liquidity AMMs

An evolution of the constant-product model lets liquidity providers concentrate their capital within a specific price range rather than the full curve, dramatically increasing capital efficiency near the current price at the cost of requiring more active management — since a position stops earning fees entirely if the price moves outside the chosen range. Our guide on providing liquidity on Uniswap and our deeper look at concentrated liquidity positions cover this model's mechanics and trade-offs.

StableSwap / hybrid invariant AMMs

Designed specifically for assets expected to trade near the same value — different stablecoins, or wrapped versions of the same underlying asset — this design blends a constant-sum formula (ideal for assets at parity) with a constant-product formula (which still functions if the assets drift apart), achieving dramatically lower slippage for in-range trades than a standard constant-product pool would. See our detailed StableSwap invariant explainer for the underlying math.

Weighted / multi-asset AMMs

Generalizes the constant-product idea beyond two assets and beyond equal weighting, allowing pools with multiple assets in custom ratios that function simultaneously as a trading venue and a self-rebalancing portfolio. Our Balancer explainer covers this design and its trade-offs in depth.

Order-book-style and hybrid on-chain models

Some DEXs, particularly for derivatives and perpetual trading, use designs closer to a traditional order book or a pooled counterparty model rather than a pure AMM curve, aiming for tighter pricing and lower slippage on large trades at the cost of different liquidity provider risk dynamics. Our comparison of GMX vs. dYdX covers this territory for perpetual futures specifically.

Comparing the main AMM families

AMM type	Best suited for	Capital efficiency	LP management needed
Constant-product	General volatile pairs	Lower — spread across full curve	Minimal
Concentrated liquidity	Any pair, with active management	High near current price	Active — range monitoring
StableSwap/hybrid	Correlated/pegged assets	Very high for in-range stable trades	Moderate
Weighted multi-asset	Custom portfolios, non-standard ratios	Moderate, varies by weighting	Moderate
Order-book/hybrid	Derivatives, large trades needing tight pricing	Depends on design	Often passive for LPs, active for market makers

Impermanent loss varies by design too

Impermanent loss isn't uniform across these models. It's most pronounced in constant-product and concentrated liquidity pools holding two uncorrelated, volatile assets, and much smaller in StableSwap-style pools holding assets that should track each other closely. Read our full impermanent loss explainer before choosing which pool type to provide liquidity to, since the "best" AMM design for you depends entirely on the asset pair and your tolerance for active management.

How fees and incentives factor into the decision

Beyond the underlying formula, the fee tier a pool charges — and whether it offers additional reward token incentives on top of trading fees — meaningfully affects which design actually produces the best return for a liquidity provider. A lower-fee tier on a highly correlated pair can still generate strong returns purely through volume, since low slippage attracts more trading activity; a higher-fee tier on a volatile pair compensates liquidity providers for the additional impermanent loss risk they're taking on, but only if enough volume actually materializes to justify it. Incentive programs layered on top, as covered in our yield farming guide, can temporarily make a design look more attractive than its underlying fee economics alone would suggest — worth checking whether a pool's advertised return depends heavily on temporary emissions rather than organic trading fees.

Evaluating protocol maturity alongside the math

The underlying formula is only part of the picture — how long a specific AMM implementation has operated, how many independent audits it's undergone, and whether it has a track record of handling edge cases (extreme volatility, thin liquidity, oracle disagreements) safely all matter as much as which mathematical model it uses. A newer AMM design with theoretically superior capital efficiency isn't automatically the better choice if it hasn't been tested under real market stress the way an older, simpler design has.

Bottom line

There's no universally "best" AMM — constant-product pools offer simplicity for general pairs, concentrated liquidity maximizes capital efficiency for those willing to manage positions actively, StableSwap-style designs dominate for pegged assets, and weighted pools suit custom multi-asset exposure. Match the AMM design to the specific asset pair and your willingness to actively manage a position, and check current DEX liquidity and yield data before committing capital to any pool.