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Lei Yang Σ:
Chief bunny feeding officer at @megaeth_labs. Recent PhD graduate from MIT CSAIL. Working on computer networks and distributed systems (for blockchain).
Lei Yang Σ: reposted
We have never asked for revenue or advisory shares from any @0xMegaMafia teams.
The only time token buybacks were mentioned was when teams asked for structural advantages such as early colocation and asset issuance, which would have been unfair to other builders in the ecosystem.
In this situation, token buyback is justified because the community needs to benefit from us giving these advantages to projects.
Everyone can build on MegaETH.
36.85K
Updating the state root is crazily slow and is responsible for an up to 10x slowdown when building EVM blocks. SALT is MegaETH's solution to this problem.
SALT is a brand new authenticated key-value store that replaces (instead of being a mere reimplementation of) EVM's Merkle Patricia Trie (MPT). It is optimized for just one thing: take as little space as possible so as to fit in computers' RAM.
This goal is supposedly easy to achieve by tuning the MPT and making it wide and shallow, but to think so one overlooks a key issue: key sparsity. Our theory + experiments (lots of details in the talk) show that sparsity inflates the sizes of MPT and friends (such as the venerable Verkle Tries, unfortunately) by hundreds of times. Consequently, they have to overflow to slow and clunky hard drives which kills performance. (Remember the 10x slowdown?)
By taming sparsity, SALT is able to get infinitely close to optimality. In fact, it is optimal in space and IO usage! The bottleneck of updating state roots has been solved once and for all.
Check out the recording of the talk! The talk was presented at the Science and Engineering of Consensus workshop during SBC 25. Huge thanks to the Tse Lab at Stanford University for organizing the event, and to event sponsors @babylonlabs_io and @poddotnetwork!
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These are some interesting results. It's always nice to see MegaETH comes on top : )
To put the data in some context, the end-to-end latency of an RPC request consists of three components: (1) speed-of-light propagation latency from/to the observer to/from the server, (2) time it takes for the server to grab and postprocess the requested data, (3) time it takes for the observer to download the response. As you mentioned, the RPC methods being tested are on the lighter side, both in terms of computational cost and in terms of data size. This means the experiments mainly tested (1), i.e., the propagation latency between observers and the RPC servers. Don't get me wrong–MegaETH's RPCs are also pretty strong on (2) and (3) and it would be interesting to see experiments that stress them!
So, how do we fine-tune the propagation latency? Actually, there are not too many knobs. First, we can deploy RPC servers in multiple geographical regions, and automatically route request to the closest server. This is like fast food chains opening shops all over the place–there is always a branch nearby! More precisely, having geo-distributed servers reduces the physical distance between users and servers.
Second, we can optimize the network topology. Even if it is between the same pair of sender and receiver, the propagation latency varies based on the actual network path traversed. For example, between US East Coast and Asia, latency can vary by 2x depending on whether the data packets go through the Pacific or through Europe. Sometimes, there are even multiple network paths following the same geographic route; some are more congested than others which induce higher latency. This is like having multiple highways to choose from point A to point B. The latency advantages you observed most likely came from us optimizing the route.
Aug 15, 21:38
MegaETH Official RPC vs Thirdweb RPC – Testnet Latency
I wanted to pull direct data from the MegaEth without having to run any infra and was looking for the fastest way to do this.
I used "" to run a simple benchmark to see how MegaETH’s official RPC compares to a third-party RPC (Thirdweb). The goal was to check which one would pull fresh data from the explorer faster from different parts of the world.
The test used the `eth_blockNumber` and the `eth_getBalance` RPC call on MegaETH testnet. It hits 27 AWS regions across 6 continents, sending requests one after the other with a one second gap. It tracked average latency, failures, 429 errors, successful requests, and total request duration.
Here are the results
All results showed that the official MegaETH RPC was faster in all six continents and all 27 regions. Latency for MegaETH ranged from about 126 ms to 238 ms according to this test. For Thirdweb latency ranged from about 170 ms to 381 ms. Both had low failure rates but MegaETH had slightly fewer, and the total request duration was consistently lower for MegaETH.
For context, typically networks have at least a few regions where a third-party RPC is faster. Avalanche, Optimism, and Ethereum all have examples of this in public benchmarks. See the
- Avalanche C-Chain results
- Optimism results
- Ethereum results
MegaETH beating Thirdweb everywhere is not typical.
My thesis on why MegaETH Official rpc comes out top is that the network is well tuned architecturally , and uses a single sequencer at a time.
I invite @NamikMuduroglu @yangl1996 @0xSami_M to share their thoughts
This is testnet so the numbers could shift on mainnet when traffic is heavier. However for now, if you need the fastest and most reliable way to pull data from the MegaETH explorer, the official RPC is the clear choice.
NB: I am not an expert, tis is just theoretical and may not be 100% accurate as the data tested were lightweight calls, also these results were snapshotted, results may vary if larger data is involved at different times, lastly i used a public thirdweb rpc, there could be other faster ones.
12.57K
Tap tap, the Robinhood moment for crypto is coming!
Aug 8, 00:43
100 of the sharpest minds in crypto just placed the same bet.
We assembled a handpicked coalition of elite builders, traders, and power users to back the breakout consumer app our industry has been waiting for.
What Robinhood did for tradfi, Euphoria will do for crypto.
Tap Trading is coming 👇🧵
2.54K
Had a very productive flight back from Copenhagen (thanks to the fact that the seat next to me was empty)!
Managed to figure out a mathematical model that explains why MegaETH's new state trie data structure is scalable while MPT and its variants are not, however optimized their implementations are. This includes Verkle tries which were given quite some hope in speeding up state root update, as well as the various DBs optimized for MPT.
I picked up the technique used in the analysis – approximating a random process with exploding state space using a memoryless process – when working on the rateless IBLT paper. It's an elementary technique, but it feels very fulfilling to successfully use the technique somewhere else!
I will introduce the new data structure at the Science and Engineering of Consensus workshop ( during SBC. It will be the first time we talk about it in details even though it has been in prod on the testnet since day 1 : ) See you there!
31.59K
Having a lot of fun migrating MegaETH to EigenDA V2 and cannot be more excited. The new architecture is elegantly minimal and composable. The simplicity leaves ample room for further scalability and graceful upgrades. It's been an especially fun experience working with Bowen on the EigenDA side on all of our crazy benchmark experiments!
@sreeramkannan and I had a few conversations on optimal DA architecture during the summer of 2022 after our DispersedLedger paper. We concluded that it's possible to build a hyper-scale DA fully decoupled from consensus. It's so exciting to see all the ideas being available in a production system!!!
Jul 30, 2025
Today, on @ethereum's 10th anniversary, we’re launching EigenDA V2 with 100 MB/s throughput, making it the first data availability solution to break the THREE-digit barrier.
As Ethereum enters its second decade, we’re proud to help scale its next wave of innovation.
Learn more 🧵
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