A tiny cluster of Solana bots unlocked a 3x trading advantage by routing through one proprietary protocol
The 62.3% versus 21.01% split covers one 12-address MEV-like group and shows association, not causation.
Quick Take
- HumidiFi-invoking transactions had positive WSOL changes 62.3% of the time, versus 21.01% for others.
- The result covers one 12-address bot cluster and shows correlation, not that HumidiFi caused the gap.
- A separate 102-address cluster routed 80.9% of its activity through the Pump.fun ecosystem.
New research into automated trading on Solana found a nearly threefold difference in positive wrapped SOL outcomes inside one small group of bots. Transactions that invoked HumidiFi, which the paper classifies as a proprietary automated market maker, recorded a positive WSOL balance change about 62.3% of the time. Other transactions in the same 12-address group did so at a 21.01% rate.
The comparison covered 244,733 HumidiFi-invoking transactions, including 152,502 with a positive WSOL balance change, and 218,678 other transactions, including 45,949 with a positive change. The rate ratio was about 2.97.
The edge appeared in one narrow cluster
The ASE 2026-accepted paper examined 200 addresses associated with two trading-oriented bot services on the Solana network. The researchers selected the top 100 addresses linked to Trojan and the top 100 linked to SolanaMevBot, then collected their transactions from Oct. 1 to Nov. 1, 2025. They grouped 158 addresses into four clusters using measures such as transaction intensity, execution success, fees, and asset breadth, while treating 42 addresses as noise.
The paper also studied 586 public bot repositories, but that software sample was built separately and cannot be connected to the 200 on-chain addresses. Its authors published a replication package through Zenodo.
Transaction-pattern reviews and service labels supported treating three clusters, totaling 56 addresses, as MEV-like. In this context, that meant the bots showed round-trip, cross-venue trading patterns consistent with arbitrage. WSOL appeared in 70.90% to 99.94% of transactions across those groups, but each cluster used a different venue mix.
The 12-address group at the center of the profit-rate comparison routed heavily through Jupiter and also invoked proprietary AMMs including HumidiFi. The researchers identified venues from the programs called inside each transaction and mapped those program IDs using Solscan annotations. They said the routes may involve closed or specialized liquidity, but did not determine why the HumidiFi-linked transactions performed differently.
The study's profit measure was a change between pre-transaction and post-transaction WSOL token balances. It was not a fully netted account of strategy returns that isolated fees, tips, timing, address behavior, route choice, or other potential differences. The data show a correlation within this cluster, not proof that HumidiFi access caused the gap.
A separate 102-address trading-operations cluster concentrated 80.9% of its activity on the Pump.fun ecosystem. Venue choice sharply separated the sampled bots' activity, even on one blockchain.
CryptoSlate has previously examined Solana's subsidies for professional trading flow, bot-related congestion, and sandwich attacks on retail users. This study does not connect HumidiFi or the sampled bots to those harms.
For ordinary DEX users, the finding suggests that participants on one chain can encounter different opportunities when their routing, infrastructure, or venue set differs. The study did not compare retail fills, slippage, or losses, so it cannot show that public-interface users were directly harmed. The measured transactions nonetheless reveal materially different conditions inside the sampled execution paths.
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