Jito’s MEV-boosted client adoption & impact on Solana validators performance

Published 6 March 2023 · Updated 6 March 2023

Maximal extractable value (MEV) is the additional value that DeFi ecosystem participants (MEV searchers) can extract by influencing transaction inclusion and ordering in blocks produced by validators. Activities such as arbitrage, front-running, NFT sniping, sandwich trading and collateralized positions liquidation present in any DeFi ecosystem contribute to the MEV. Searchers are willing to pay extra fees for priority access to MEV opportunities. These fees ("MEV rewards") can generate significant amounts of additional revenue for validators and their delegators.

The Jito client, which was launched on Solana mainnet-beta in October, 2022, is the first third-party validator client for Solana which represents a significant improvement to Solana's validator software. Jito software enables more efficient transaction and bundle processing helping both validators and searchers effectively identify and exploit MEV opportunities while eliminating unproductive network spam. It allows validators running the Jito client and their delegators to earn additional revenue from MEV through the Tip Distribution on-chain program which collects and distributes the fees (or “tips”) in proportion equal to a commission set by a validator. The client adoption is good for the Solana ecosystem because it can increase the network's stability, incentivize more validator operators and stakers to join, and help Solana to become more attractive to DeFi ecosystem participants.

This article will explore statistics on the Jito client adoption within the Solana mainnet-beta cluster, such as the growth of the number of validators running the Jito client, their total active stake and market share. We will also explore the dynamics of MEV rewards generated and compare the performance of Jito validators with that of the rest of the cluster. Additionally, we will investigate whether the adoption of the Jito client has a significant impact on the performance of validators who started to use it. Through this analysis, we aim to shed light on the potential benefits and drawbacks of using the Jito client for validators operating within the Solana network. The data used in this report is publicly available through the P2P Validator public dashboard at: https://reports.p2p.org/superset/dashboard/jito_client_adoption/.

The Jito client adoption

The Jito client has been gaining traction among Solana validator operators, as reflected by the growing number of Jito validators (see the left chart in the figure below).

The significant increase in the number of Solana validators using the Jito client indicates a growing recognition of the software's advantages among operators.

The number of stakers receiving MEV rewards from Jito-enabled validators (the right chart in the figure above) is showing a positive trend, with two anomalies observed in epochs 385 (+84,075 stakers) and 404 (-82,420 stakers). These anomalies can be explained by the fact that during the epoch 385, the Everstake validator started using the Jito client, and then stopped doing so during the epoch 404, resulting in a sharp change in the number of stakers receiving MEV rewards.

The table below shows that a few validators have discontinued using the Jito client, with Everstake validator being the most notable among them. The reasons for these validators stopped using the client are unclear as there were no significant changes in the validators performance during the usage of the Jito client.

Such important metrics measuring the Jito client adoption as total active stake and market share of validators running Jito client have significantly increased over the last ~50 epochs (as seen in the left and right charts in the figure below). The more active stake the validators running the Jito client have, the more slots are processed with the Jito client, and the more MEV opportunities become available for efficient utilization and redistribution

The trend of decreasing average active stake per validator using the Jito client (see the middle chart in the figure above) indicates that more validators with smaller stakes are adopting the software. The increasing trend of Jito client adoption among smaller validators is a positive sign, indicating that even smaller validators can successfully run the software. The Jito client democratizes access to MEV with equal treatment for all validators. The growth in adoption by lower-stake validators demonstrates a strong interest in MEV opportunities from a community that was previously unable to access these benefits.

The Jito-related MEV rewards currently are very low (as seen in the figure below), which can be attributed to the current limited adoption of the client and lack of participation from MEV searchers. However, a sudden MEV rewards level change after epoch #403 cannot be solely attributed to the increase in the number of validators using the client or the growth of Jito-related active stake. This indicates that a relatively large DeFi ecosystem participant might have started leveraging the MEV extraction tools offered by Jito. As the Jito client gains validator market share, MEV searchers may see more benefits from integration and MEV rewards could rise.

The share of MEV rewards taken by validators running the Jito client has recently increased from about 8% to 21.5% (see figure below). This is mainly due to new validators setting their MEV rewards commission rate to 100%, with many of them being unnamed validators taking 100% stake rewards commission, such as private or white label validators.

Performance of the validators running the Jito client vs. others

The comparison of performance metrics between validators using the Jito client and those who are not is important to gain insights into the differences between the two groups and understand the potential impact of the Jito client on the Solana network.

Based on the chart below (see figure below), it appears that, on average, Jito validators have better uptime than other validators. This outcome is likely due to the fact that more experienced validators are more likely to experiment with the new Jito client software, while Solana also has a significant number of inexperienced validators with small stake who may not have yet developed the skills or infrastructure necessary to maintain high uptime.

There are outliers for some epochs where the average uptime for Jito validators dropped significantly which is due to a specific validator named “DO NOT DELEGATE” with the vote account pubkey Dn2cRSWAfQpb3NyUJ2q33t1scBLxzo8TZBAyKsWhX7zh, which experienced downtime for 2700 minutes during that epoch and also experienced several very long periods of downtime in other epochs.

The average vote success rate chart displayed below (see figure below) indicates that Jito validators also generally earn more vote credits for their participation in Solana consensus compared to all other validators. However, due to the metric's volatility, the difference seems insignificant.

The chart below (see figure below) displays the dynamics of the stake-weighted average block production rate for Jito validators and others, indicating a significant difference in favor of Jito validators. This suggests that the Jito client may indeed optimize transaction block processing.

Performance changes after adopting the Jito client

In the previous section, we visually compared the performance metrics of validators running the Jito client and those who are not and observed that there could be statistically significant differences between the two groups. However, the observed differences cannot be solely attributed to the client switch and suggest that other factors may be at play. For instance, early adopters of the Jito client may have more experience in operating validators, and there may be differences in hardware configurations, network connection, or operating conditions that affect performance. Additionally, there are over 2000 Solana validators not running the Jito client, many of which may be operated by inexperienced operators using cheaper hardware, which could further contribute to the observed performance differences.

In this section we estimate the impact of adopting the Jito client on the performance of Solana validators by comparing their performance metrics before and after adoption, while considering the unique characteristics of each validator. Due to the considerable variation in metrics epoch over epoch caused by external factors, the data was normalized by dividing their values in each epoch by the corresponding epoch average. This normalization method enables a better comparison of validators' relative performance over time and accounts for external factors that greatly impact the metrics for each validator in the cluster. The normalized metrics for each validator before and after the Jito client adoption were averaged to form two samples, which can be compared using the Wilcoxon signed-ranks test. By using the test on the averaged normalized data, we determined whether the adoption of the Jito client had a statistically significant impact on the performance metrics of Solana validators. To ensure sufficient statistical data for both periods, we only compared the performance metrics of 52 validators who ran the Jito client during 25% to 75% of the observed epochs (from 345 to 415). Comparing the relative uptime of validators before and after adopting the Jito client one can observe (see figure below) that the distribution of relative uptime before adoption is wider and has a heavier right tail.

Using the Wilcoxon signed-ranks test, we found strong evidence (N = 52, V = 371, p < 0.01) that adopting the Jito client had a small negative impact on the relative uptime reducing the median by ~1.9 p.p. (from 105.8% to 103.9%).

It's possible that the negative impact on relative uptime is due to the fact that the software is relatively new and still undergoing updates and improvements. Testing of new features requires validator restarts that contribute to some of the downtime. Further research and analysis is needed to better understand the specific factors contributing to the observed differences.

Comparing the relative vote success rate of validators before and after adopting the Jito client, one can observe (see figure below) that the two distributions are almost identical.

The Wilcoxon signed-ranks test showed no significant positive impact of adopting the Jito client on the relative vote success rate (N = 52, V = 648, p > 0.05).

Comparing the relative block production rate of validators before and after the adoption of the Jito client, one can observe (see figure below) that there are significant differences in the two distributions: the distribution of relative block production rate after adopting the Jito client is centered around 120%, while the distribution before adoption is centered around 105%.

The Wilcoxon signed-ranks test showed strong evidence (N = 52, V = 946, p < 0.01) that the adoption of the Jito client had a significant positive impact on the relative block production rate of Solana validators increasing the median by ~9.4 p.p. (from 111.5% to 120.9%). The increased block production rate is likely due to the more efficient transaction processing enabled by the Jito client's optimized block engine.

Conclusion

The Jito client represents a valuable addition to the Solana ecosystem, providing validators and their delegators with a new revenue stream from MEV opportunities, while helping the Solana network to be more stable.

The Jito client has yet to gain widespread adoption, however, the number of validators utilizing the software is steadily growing, along with the total active stake and staking market share attributed to the Jito client. Some validators have stopped using the client, but they constitute a small fraction and the reasons for this are unclear.

Additionally, Jito validators and their stakers have not yet earned significant MEV rewards, which may be due to the lack of usage of the client by MEV searchers and users. This situation should improve with broader adoption of the client and as searchers become more accustomed to the new tools.

On average, validators running the Jito client have better performance than others, although statistical analysis shows that uptime of the validators currently running Jito client has slightly decreased after the switch, while vote success rate has remained largely unchanged and block production rate has increased significantly.

For those interested in exploring the data further, P2P Validator's public dashboard provides access to all the data used in the report preparation: https://reports.p2p.org/superset/dashboard/jito_client_adoption/.

Acknowledgments

We would like to express our gratitude and appreciation to the P2P Validator team members, including Pavel Pavlov, Anton Yakovlev, Steven Quinn, and Alexey Bondar , for their invaluable guidance, support, and encouragement throughout this research. Furthermore, we would like to express gratitude to the Jito Labs team, especially Brian Smith and Lucas Bruder, for their support and openness during the research. We would also like to thank Brian Long and his team for creating the Validators.app API.

Sources

Overall information on Jito & MEV:

Dashboards:

Data sources / APIs:

Pavel Marmalyuk

Data analyst @ p2p.org (previously dentsu inc.), graduated from Moscow State University of Psychology and Education, PhD, father, blockchain enthusiast & investor.