route99.xyzroute

DEX aggregator rankings

Even the best aggregators miss more than 1 in 1,000 swaps. route99 grades them live for your goals and finds the combination that reaches 99.9% reliability.

A shortcut — or build your own set by clicking rows in the table below. More independent sources means one can cover another's misses.
Simulate every quote against live state and rank by verified output — this filters out no-quotes, sim failures and overquoting before anything is sent. Without it, sim-failure becomes revert rate.
Target: 99.9% chance at least one quote arrives in time.
RELIABILITY
99%
99.9% target
98.0%99.0%99.9%100%
How it's computedThe full math behind the number, step by step

Rankings for your setup

Enso's measured values, unchanged. The colour bands shift with your setup: with more redundancy, no-quote and sim-failure relax; without simulation, sim-failure hard-pins to the revert bar; latency grades against your budget. Click any row to add or remove it from your set — the highlighted rows are what the reliability above is computed on. Auto-pick seeds a starting set; then it's yours to edit.

Aggregator Score1–10 · weighted Overquoteprice holds Quote→fill gapavg drift Sim failurereverts No-quoteavailability Median lat.speed p95 lat.tail
strong for this setup borderline weak for this setup META = meta-aggregator (routes across other aggregators/bridges, not direct DEX liquidity)
03

Reliability funnel.

The set you selected above, traced through each gate. Every thin line is one source draining as quotes fail to return, arrive late, or fail simulation; the bold line is the combined result — redundancy recovers what individual sources lose.

Where quotes drop, and how redundancy recovers
combined (≥1 survives) each thin line = one source draining through the gates · combined = 1 − ∏(all fail) at each step
04

Every aggregator's shape.

Six dimensions at once — further out is better on every axis. Your selected sources are drawn in colour; the rest of the field sits faint behind them. Click any shape (or legend entry) to add or remove that aggregator from your set. A round hexagon is an all-rounder; a spiky one trades strengths for weaknesses. Hover any shape for its name.

05

Quote integrity: how often × how much.

Overquote rate and quote→fill gap are two views of the same failure — a quoted price that doesn't hold. This map separates them: horizontal = how often quotes are inflated (log scale), vertical = how far fills drift on average. Bottom-left is honest and tight; top-right quotes wrong often and by a lot. Click any dot to add or remove it from your set.

Overquote frequency × fill drift
selected — bold, larger unselected — smaller, gray dashed lines mark the green bands (1% · 0.5 bps) · axes clamp at the plot edge
Average overquote cost per trade

A little drift is normal: prices move in the milliseconds between quote and fill, so a few hundredths of a bp reflects latency, not padding. It becomes a cost signal past the 0.05 bps noise band.

within latency noise (≤0.05 bps) above noise (≤0.4 bps) costly (>0.4 bps) avg quote→fill drift in bps, priced per $1M swapped · shaded zone = latency noise (≤0.05 bps) · bold = in your set
06

Latency against your budget.

A quote is only usable if it arrives in time. With one source you need the p95 inside budget; with several, the median is enough because the fastest of many arrives first. The line marks your current budget.

median (first number) p95 tail (second) not in your set · click a row to add/remove your budget bars past the line don't reliably arrive in time · chip = % of quotes arriving in time (availability × speed; = availability when budget is off)
Speed × integrity — the same trade-off as one picture
selected — bold, larger unselected — smaller, muted ↑ more honest · → faster · click any dot to add/remove from your set
07

Network coverage.

Execution quality is only half the picture — an aggregator also has to support the chains you ship on. There's no single registry of this, so counts come from each provider's own source, in order of strength: where a provider exposes a machine-readable chain registry (Nordstern, LI.FI, Fly, Odos), this page fetches it live in your browser and counts mainnets directly; otherwise the count comes from the provider's official docs; headline claims are marked self-reported, and anything unconfirmed is flagged unverified.

live registry · counted in your browser official docs self-reported unverified chains supported for swaps · sources linked per row · docs verified 21 Jul 2026 · live registries re-counted on page load
08

What the API costs.

Execution quality is one axis; what you pay is the other. Cost stacks in layers: a monthly subscription (if any), an explicit platform fee in bps, and hidden buckets (gas treatment, bridge/LP fees). This compares the published layers — set your monthly volume and see the effective monthly cost where providers disclose enough to compute one. Undisclosed pricing is shown as exactly that, not assumed zero.

Effective monthly cost = subscription + fee × volume
published range (min–max) not publicly disclosed provider docs & pricing pages, Jul 2026 · explicit fees only — excludes gas, bridge/LP fees & your own integrator fee
09

Method & source.

All measurements are produced by Enso Shield — an independent benchmark that quotes every aggregator on the identical swap and re-simulates against live chain state (methodology ↗). DFC Research changes none of the numbers; we only re-grade and re-plot them for a given integration setup.

The reliability model. Each source yields a usable quote if it arrives in time and — when simulating — passes simulation. Arrival is estimated from Enso's median and p95 via a log-normal fit. With independent sources, the request fails only if all miss, so reliability = 1 − ∏(1 − uᵢ). The green band for redundancy-covered failures (no-quote; sim-failure when simulating) is 0.001^(1/N): the per-source rate at which N sources still clear 99.9%. Without simulation, sim-failure becomes revert rate directly and redundancy can't mask it, so it hard-pins to 0.1%.

The honest limit. This assumes source failures are independent. Correlated failures — honeypots, transfer-tax tokens, genuinely illiquid routes — fail every source at once and set a floor no amount of redundancy clears. Reaching sub-0.1% in practice is two jobs: enough fast, honest, independent quotes (modelled here) and pre-trade filtering to remove intrinsically unexecutable routes (not in this dataset).

Independence: DFC Research is not affiliated with any of the measured aggregators. Presentation is kept even-handed and the source is linked throughout so any figure can be verified directly against Enso.