GMGN leads on 1 of 4 shared benchmarks, pump.fun on 3. GMGN wins on Trading app daily volume 2026 ($84.94M vs $31.06M). pump.fun wins on iOS App Store rating (4.73x vs 3.63x), Solana DEX volume ($210.79M vs $33.60M), Trading terminal fill quality 2026 (232 bps vs 345 bps). Data as of 2026-09-27 UTC.
Read methodology Last measured Window: rolling 24h5 shared benchmarks, 4 measured on both sides
GMGN is a Solana and EVM memecoin trading terminal combining wallet tracking, smart money copy trading and a Telegram bot. It routes swaps through pump.fun and DEX pools with a configurable slippage and fee.
pump.fun is the leading Solana memecoin launchpad. Tokens start on a bonding curve and graduate to PumpSwap (pump.fun's native AMM, launched March 2025) when the curve completes.
Volume is what each app's DeFiLlama dexs adapter attributes to it per UTC day, over every chain that adapter covers. Commission is the app's own cut from its fees adapter (dailyRevenue), not the total fees paid on the trade: the venue underneath takes its own share, and counting that would roughly double the figure. The take rate divides the two over the same days, so it is a floor where an adapter covers fewer chains for fees than for volume. Rows end on each app's own latest closed day.
Ratings reflect the current all-time average user rating from the Apple App Store as returned by the iTunes lookup API. Apple does not expose star-distribution breakdowns or time-windowed averages via the public API. A high rating with few reviews carries more statistical uncertainty than the same rating with tens of thousands of reviews. The review count column shows how many users contributed to each rating.
Volume and revenue from DeFiLlama's DEX and fees APIs, 24h and 7d totals refreshed every 30 minutes. Terminal volume is a floor: a swap counts only when its transaction pays the terminal's fee wallet and Dune decodes the venue. Revenue (dailyRevenue, LP fees stripped) counts every fee reaching those wallets. Their ratio is a take rate this bench does not rank on: it moves threefold across a fortnight for one app. Bench 201 publishes it daily. Terminal and launchpad volume are not additive.
Volume is what each app's DeFiLlama adapter attributes to the app per UTC day, over every chain the adapter covers: FOMO is Solana only on DeFiLlama, GMGN spans ten chains. Each row ends on the app's latest closed day: most adapters are Dune queries that publish a day 10 to 20 hours after it closes, so before mid-day UTC some rows are dated one day behind, and GMGN's adapter skips some days. DeFiLlama can restate the last day for about a day; the series is re-read hourly.
Random sample (150 a day per row, Solana and EVM alike) of the swaps each terminal routed, every attempt counted for the fail rate. Reference = the pool's state before the swap (its reserves, or the previous trade within 60 s); swaps without one keep their split, no loss figure. Published from 50 priced swaps pooled over the product's chains at 25 or more (a single-chain product from 25), ranked from 100; the median's 95 % interval is in the JSON. Compare medians, not single swaps.
Frequently asked questions
GMGN vs pump.fun: which one is better?
GMGN and pump.fun are compared on 5 shared OpenChainBench benchmarks. GMGN leads on Trading app daily volume 2026. pump.fun leads on iOS App Store rating. See the live table on this page for every metric.
Which has the higher daily volume, GMGN or pump.fun?
On the Trading app daily volume 2026 benchmark, GMGN leads at $84.94M versus pump.fun at $31.06M. Live measurement is updated continuously by the OpenChainBench harness.
Which is higher-rated, GMGN or pump.fun?
On the Crypto trading app iOS App Store ratings, live benchmark, pump.fun leads at 4.73x versus GMGN at 3.63x (provisional). Live measurement is updated continuously by the OpenChainBench harness.
How is the GMGN vs pump.fun comparison measured?
Every benchmark on this page uses the same open methodology, published at https://openchainbench.com/methodology. Data is CC-BY-4.0. Measurement harnesses are MIT-licensed.
Auto-generated pairs require: both providers in the same benchmark for seven consecutive days, at least 1000 samples per provider, observable third-party search demand, and a public /products/[slug] page on OCB. Editorially curated pairs (like this one) may publish early when search demand is high and data is accruing; panels with fewer than 100 samples are shown as provisional. The full pair ledger is versioned in the public repo.
