Jito, a leading Solana dApp, unveiled the IBRL Explorer, a tool designed to provide transparency into validator behavior and block production.
For years, the inner workings of Solana blocks have largely been a black box, making it difficult for users and applications to understand network performance. The IBRL Explorer changes that by measuring key validator metrics. It highlights inefficiencies, and giving the community actionable insights.
Late Packing and Slot Timing Games: Whatβs at Stake
During internal testing, Jitoβs team discovered widespread late packing, a practice where validators concentrate transactions at the end of a block slot. Solana is built as a streaming system, and validators are expected to distribute transactions evenly throughout the slot while broadcasting data over the Turbine protocol. Late packing delays state updates, increases execution variance for liquidations and auctions, and reduces network efficiency.
Imagine a world where you can actually see whatβs happening inside a Solana block.
Up until now this has largely remained a mystery, but that changes today!
ππ»ππΏπΌπ±ππ°πΆπ»π΄ ππ΅π² πππ₯π ππ π½πΉπΌπΏπ²πΏ!
π§΅π pic.twitter.com/w71igMxSXC
β Jito (@jito_sol) January 5, 2026
Another common problem is slot timing games. Validators can tweak their Proof of History parameters to extend slot times beyond Solanaβs default 360 milliseconds. Slot lagging slows state transitions, increases end-to-end latency, and reduces application reliability. Both late packing and slot timing games can cascade through the network, causing validators to replay data late and vote late, which affects the entire ecosystem.
IBRL Explorer Scores Solana Validators, Reveals Network Trends
The IBRL Explorer introduces the IBRL Score, which evaluates validator performance using three metrics: slot time score, vote packing score, and non-vote packing score. The slot time score rewards validators who produce blocks quickly. The vote packing score incentivizes timely processing of vote transactions, and the non-vote packing score evaluates whether transactions are evenly distributed through the block.
12/ Itβs time to IBRL/acc!
The IBRL Explorer exists to create a shared source of truth.
Providing measurable, transparent, and auditable data on validator behavior.
Start exploring today!https://t.co/gaIJl0fmng
β Jito (@jito_sol) January 5, 2026
Since its internal launch, the IBRL Explorer has already highlighted real-world network trends. For example, Jito observed unintentional late packing of votes across data centers in Tokyo, Singapore, and other regions in Asia. Likely due to submarine cable disruptions. Another trend revealed the ripple effect caused by late packing non-vote transactions, where delays by one validator propagate across the network.
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