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- Nidhi Kolhapur
Nidhi Kolhapur
Nidhi is a Certified Digital Marketing Executive and Passionate crypto Journalist covering the world of alternative currencies. She shares the latest and trending news on Cryptocurrency and Blockchain.
- Reviewed by:
Zafar Naik - Oct 18, 2025 11:14 UTC
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Vitalik Buterin Proposes New Way to Measure Ethereum’s Crypto Performance
Vitalik Buterin proposes a new “efficiency ratio” to measure cryptographic performance
The efficiency ratio compares computation time with cryptography versus raw computation time, providing a clearer view of performance overhead.
Challenges remain due to heterogeneous operations, parallelization, and memory patterns
Ethereum is exploring new ways to measure and improve performance of cryptographic systems.
Co-founder Vitalik Buterin is now calling for a shift in how developers assess cryptographic systems like zero-knowledge proofs (ZK) and fully homomorphic encryption (FHE), aiming to provide them with more meaningful metrics.
Buterin Proposes New Efficiency Metric
Traditionally, cryptographic performance has been measured in “operations per second” metric, which can be hardware-dependent and sometimes misleading. Instead, Buterin proposes using an “efficiency ratio”, the ratio of computation time when using cryptography versus raw computation time.
He notes that this approach is less dependent on hardware, showing clearly how much efficiency is lost by making an app cryptographic. It also makes estimating performance simpler, since developers already know how long the raw computation takes.
The Challenges of Measuring Cryptography
Vitalik also admits that this is hard because the operations involved are heterogeneous as execution and proof steps can vary, especially with differences in parallelization (SIMD) and memory access patterns. So even a ratio can still be affected by hardware to some extent.
Despite these limitations, he believes the overhead factor is still a useful and meaningful metric for evaluating cryptographic performance.
Crypto researcher Lukas Helminger asked how to benchmark the overhead of fully homomorphic encryption (FHE) or multi-party computation (MPC), noting that it’s more complicated than in zero-knowledge proofs. He also wondered which network assumptions or number of parties should be considered when calculating the overhead.
Buterin explained that FHE is mostly a single-party process, so network considerations have little impact. Only minor steps like sending inputs or performing threshold decryption matter, and these are negligible compared to computation time.
Helminger noted that real-world blockchain scenarios could see extra overhead when many nodes are involved. Buterin agreed but said raw runtime in a deployed setting still provides the clearest picture.
Ethereum Scaling Breakthrough
Just recently, Brevis unveiled Pico Prism, a high-performance zkVM for real-time Ethereum block proving. With 64 RTX 5090 GPUs, it proves 99.6% of blocks in under 12 seconds, averaging 6.9 seconds.
This breakthrough could boost Ethereum’s scalability by up to 100× and move toward a future where anyone could validate the blockchain even from a smartphone. Buterin also highlighted it as a major advancement in ZK-EVM proving speed and diversity.
Ethereum’s Ambitious zk-Powered Future
Crypto investor Ryan Sean Adams highlights how Ethereum is taking a radically different path from other blockchains.
He sees it evolving into a zk-powered chain, where Layer 1 handles global DeFi with high throughput (10,000 TPS) and nodes lightweight enough to run on a phone. Layer 2 networks will handle everything else, including general-purpose applications like Base or Arbitrum as well as appchains like lighter.
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FAQs
It’s challenging because different operations and their ability to run in parallel can vary, making a single metric hard to define. Hardware can still influence the results.
For FHE, the overhead is almost entirely from computation, not network delays. This makes it simpler to measure than systems requiring multiple parties to communicate.
Ethereum is evolving into a zk-powered chain where the main network handles high-value transactions, while Layer 2s manage everything else, aiming for massive scalability and light nodes.
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