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Batch V1.1 is set to be deployed on the XRP Ledger mainnet in just five days. Batch V1.1 is a replacement amendment that ships the fixed Batch implementation in xrpld v3.3.0.

According to XRPScan data, Batch is set to activate on October 9, 2026, the same day as the fixBatchV1_2 amendment, after its activation timer was reset.

Batch had earlier gained majority and was set to activate on September 29, 2026. This timing shifted after the amendment was temporarily rejected to restart the two-week activation window.

As reported, a minor issue was detected with the fix included in the xrpld 3.4.1 release; the XRP community subsequently flipped their votes to allow Batch to simultaneously launch with its fix update.

Batch (XLS-56) allows multiple XRPL transactions from multiple accounts to be executed atomically in a single ledger close. If an inner transaction fails in the all-or-nothing mode of the feature, the entire batch is rolled back.

Batch is required or serves as an accelerant for several high-value XRPL use cases already under contract or in active pipeline, such as atomic multi-party settlements.

In line with XRPL's consensus process, amendments must maintain two weeks of support from more than 80% of trusted validators to be enabled.

If support drops below 80%, the amendment is temporarily rejected, and the two-week period restarts. Given the past setbacks it faced, the Batch feature launch is a significant milestone for the XRP community. If everything goes well and support remains above 80%, Batch will be launched.

What's next?

The permission delegation amendment is expected to arrive on the mainnet in the next four days, on October 8, 2026.

At the recently concluded XRP Seoul event, RippleX head of engineering JA Akinyele shared a keynote on what is being built into the XRP Ledger to support the next wave of developers, institutions, and users.

To handle the growing demand for complex financial operations on-chain, the XRPL architecture is undergoing rigorous upgrades that include formal verification, adversarial testing, and new structural features like transaction batching, which enables bundled, all-or-nothing operations to boost system efficiency and developer scalability.