Backpack Cuts Tokenized Stock Costs by Half vs xStocks via Prop AMM

Woofun AI reports that Backpack’s proprietary Automated Market Maker (AMM) infrastructure has fundamentally altered the cost structure for trading tokenized U.S. stocks on Solana, delivering execution prices approximately half those of its primary competitor, xStocks. This divergence in efficiency stems not from differences in headline trading volume, but from distinct market structures: Backpack relies on internal market makers to provide continuous liquidity, whereas xStocks depends heavily on public pools characterized by high circular flow and wider spreads. The analysis reveals that while both platforms operate within the same blockchain environment, their approaches to liquidity provision create a significant disparity in user costs, challenging the assumption that higher aggregate volume equates to better market quality.

The broader market context for these developments was marked by significant volatility and sector-specific performance disparities within the Solana ecosystem. According to analysis by Jake Koch-Gallup and Sam Schubert, compiled by AididiaoJP and Foresight News, the Solana ecosystem index surged by 8.0%, a gain that more than doubled the performance of the second-ranked asset class.

However, this aggregate increase was driven almost entirely by two specific tokens: META and PUMP. Other sectors lagged significantly behind, with Launchpad rising by 3.2%, the Bittensor ecosystem by 2.7%, AI-related assets by 2.2%, and perpetual contracts by 2.0%. This concentration of gains highlights the uneven distribution of value creation within the network, suggesting that the overall index performance may not reflect the health of the broader ecosystem.

Traditional financial assets and other cryptocurrency sectors exhibited mixed performance during the same period, further contextualizing the Solana data. The Nasdaq 100 rose by 3.0% and the S&P 500 by 1.9%, outperforming Bitcoin, which saw a modest increase of only 0.9%. In contrast, crypto mining companies suffered the steepest losses, dropping by 3.1%, while both the Ethereum ecosystem and the lending sector declined by 2.0%. On a weekly basis, the narrative shifted dramatically; despite the daily drop, crypto mining companies ranked second with a 15.1% increase. Conversely, the DEX sector, which had led earlier in the week, erased all gains to finish down by 1.1%. The lending sector performed the worst weekly, falling by 10.0%, followed closely by the Ethereum ecosystem at -9.8%. The public chain sector declined by 2.0%, with SOL trading at approximately $73, representing a 10% monthly decline.

A deeper examination of the Solana index composition reveals that the reported gains were structurally narrow and potentially misleading. Since its listing on Upbit, META has surged by 46.6% on a weekly basis, while PUMP increased by 22.9% and accounts for roughly one-third of the index’s total weight. These two tokens alone contributed nearly all of the index’s 17.8% weekly gain. Among the 11 components in the index, 7 experienced declines: BP fell by 13.7%, BONK by 7.7%, and the median component dropped by 5.4%. This disparity underscores that the ecosystem’s rise was not broad-based.

Concurrently, proposals to alter monetary policy emerged for both major chains. Solana's "Double Deflation Proposal" aims to increase the annual deflation rate from 15% to 30% and advance the terminal inflation lower bound from 2032 to 2029, which would result in approximately 18.9M fewer SOL coins being issued over the next six years. Similarly, Ethereum’s EIP-8361 proposes eliminating validator rewards for staking more than 50% of the total supply, aiming to bring net consensus issuance to zero at that threshold and reduce the current yield by roughly half to around 1.1%. Both proposals remain in draft form, and their potential impact has not yet been priced into the assets.

When comparing the trading volumes of Backpack Securities and xStocks, headline figures suggest parity, but adjusted metrics reveal a stark difference. From June 12 to July 30, xStocks reported $2.43B in transactions, while Backpack recorded $2.10B.

However, SPYx alone accounted for $1.70B of xStocks’ volume, representing 70% of its total. Much of this volume consisted of internal pool transactions rather than genuine external demand. Excluding SPYx, xStocks’ comparable trading volume drops to $726M, significantly less than Backpack’s $2.10B. This adjustment is critical for understanding the true scale of each platform’s market activity. The launch of SPCX on June 12 marked a turning point for Backpack, as it began to capture a larger share of genuine trading interest, whereas xStocks remained reliant on concentrated, potentially artificial volume drivers.

The source of liquidity further differentiates the two platforms, with Backpack’s Prop AMM dominating its transaction flow. Since the launch of SPCX, between 66% and 74% of Backpack’s weekly transactions were completed through its proprietary AMM, averaging 71% over the past four full weeks. In contrast, only about 33% of xStocks’ transactions were handled via Prop AMM, a figure significantly inflated by AlphaQ’s $284M in transactions during a single week; without that anomaly, the proportion fell below 10%. This reliance on internal market makers allowed Backpack to offer immediate liquidity, with market makers providing bid-ask quotes of $10,000 each within hours of SPCX’s launch. This rapid deployment of professional pricing mechanisms contrasts sharply with xStocks’ dependence on public pools, which often lack the depth and continuity required for efficient large-scale trading.

Trading patterns on Solana’s tokenized stock markets reveal a high degree of circular flow, particularly on xStocks. Data indicates that 69% of weekday transactions in 30-minute intervals on Backpack were completed through Prop AMM, with 80% of these intervals showing a percentage between 62% and 84%. On weekends, this figure remained robust at 64%. Market makers maintained continuous quotes, widening spreads during U.S. market closures rather than withdrawing orders.

In contrast, pool trading volume on xStocks spiked around U.S. market open and close times, consistent with arbitrage and hedging activities. Approximately 68% of transactions in Solana’s tokenized stock market are circular: 31% occur within minutes, including atomic transactions, 34.5% happen within the same day, and only 7.1% represent long-term directional positions. Despite this, the number of holders grew from 129k in May to 211k by July, with $164M in unmatched buy volume remaining as of late July.

Woofun AI data shows that execution costs for SPCX were consistently lower than those for xStocks across all measured periods. The analysis focused on transactions in the $100–$500 range from June 12 to July 20, using NBBO quotes during regular trading hours and Blue Ocean quotes for overnight periods. By comparing actual transactions from different traders within the same time frame, rather than routing the same order twice, the study isolated the true cost differential. During regular trading hours, xStocks was approximately 2.4–2.5 basis points more expensive than Backpack. This cost advantage was even more pronounced during overnight periods, where xStocks was 2.8–2.9 basis points more expensive. The methodology ensured that the comparison reflected genuine market conditions, avoiding biases introduced by self-referential trading or artificial volume generation.

The consistency of Backpack’s cost advantage is evident across both regular and overnight trading sessions. Out of 25 qualifying regular trading days, Backpack offered cheaper execution on 22 days. During the 17 overnight periods analyzed, Backpack was cheaper on all occasions. This uniformity supports the hypothesis that Prop AMMs, by competing for traffic based on real-time reference prices, can maintain tighter spreads and lower costs than public pools, which often suffer from liquidity fragmentation and wider bid-ask spreads. The ability of Backpack’s market makers to provide continuous, competitive quotes regardless of market hours demonstrates a structural advantage that translates directly into savings for users. This efficiency is not merely a temporary anomaly but a systemic feature of the proprietary liquidity model.

Ultimately, the comparison between Backpack and xStocks underscores the critical role of market structure in determining execution costs for tokenized U.S. stocks. Backpack’s reliance on Prop AMM has proven superior to xStocks’ dependence on public pools, resulting in significantly lower costs for traders. This efficiency gap highlights the limitations of relying on aggregate volume as a metric of market health, as high volume can mask underlying inefficiencies such as circular trading and liquidity fragmentation. As the market for tokenized assets matures, platforms that prioritize continuous, professional liquidity provision will likely capture a larger share of genuine trading activity, leaving those reliant on artificial volume drivers at a competitive disadvantage. This trend suggests a future where execution quality, rather than sheer volume, becomes the primary differentiator in the digital asset space.