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- Debashree Patra
Debashree Patra
- Reviewed by:
Qadir AKQadir Ak is the founder of Coinpedia. He has over a decade of experience writing about technology and has been covering the blockchain and cryptocurrency space since 2010. He has also interviewed a few prominent experts within the cryptocurrency space.
- Oct 18, 2025 12:01 UTC
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Ethereum Co-Founder Vitalik Buterin Redefines ZK and FHE Performance with ‘Efficiency Ratio’ Metric
Vitalik proposes using an “efficiency ratio” or kappa to gauge how encryption slows computation versus normal processing.
Clearer performance metrics can improve blockchain scalability, encryption efficiency, and smarter crypto development.
Ethereum co-founder Vitalik Buterin is calling on developers in zero-knowledge proofs (ZK) and fully homomorphic encryption (FHE) to rethink how they measure performance. Right now, many developers focus on “operations per second,” but Vitalik says that doesn’t give the full picture. He suggests using an efficiency ratio instead, this shows how much slower a computation gets when it’s encrypted compared to running it normally.
Making Performance Clear
Vitalik explained on X that the efficiency ratio is easy to understand and helps developers see the real trade-offs. “You already know how long a raw computation takes, so you just multiply to get the encrypted time,” he said. This makes it more hardware-independent and practical.
He also noted that the ratio isn’t perfect, things like memory access, parallel processing, and SIMD operations can affect results. Still, he believes it’s a much better measure than just saying “we can do N operations per second,” which doesn’t tell you how efficient the encryption really is.
Experts Join the Conversation
Crypto analyst Wei Dai agreed with Vitalik and called this measurement kappa. Kappa shows the extra time needed to prove a computation cryptographically compared to running it normally. Vitalik predicted that in the future, many computations could have single-digit kappa, meaning encryption would add very little overhead. He said some operations, like Poseidon hashing, are already very efficient, which is important for quantum-resistant cryptography.
Crypto user, Lukas Helminger joined the discussion, asking how to benchmark FHE overhead for blockchain use cases, where the network and number of participants could affect performance. Vitalik clarified that FHE is mostly single-party, so the network matters little except when sending inputs or doing threshold decryption. Lukas said that for blockchain applications, assuming a small number of nodes is important, because large networks could slow things down. Vitalik added that threshold decryption should be measured using bandwidth and network latency, while raw runtime is more useful for real-world estimates.
Ethereum’s Scaling Issues
Ethereum still faces challenges with efficiency. Every node currently verifies every block, which limits how much data each block can hold. Raising the gas limit could allow more transactions but also risks overloading validators, who have only a few seconds to process each block.
Meanwhile, Ethereum developer Dankrad Feist, who helped design the Danksharding system, has joined Tempo, a new Layer-1 blockchain project backed by Stripe and Paradigm. Feist is working on making networks faster and more efficient.
Why Metrics Matter
Vitalik’s push for clearer metrics is about helping developers make better decisions. By using efficiency ratios or kappa, developers can see the true cost of encryption, design faster apps, and help Ethereum scale in a balanced and reliable way. These simple measures could make a big difference in the future of crypto development.
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FAQs
A zero-knowledge proof is a cryptographic method that allows one party to prove to another that a statement is true, without revealing any information beyond the validity of the statement itself.
It’s a measure comparing how much slower a computation runs when it’s encrypted versus running normally, giving a clearer picture of cryptographic performance than raw speed.
Clearer metrics like the efficiency ratio help developers optimize apps and layer-2 solutions, reducing the computational burden on the main Ethereum network for faster, cheaper transactions.
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