Vitalik Buterin Sees 60% Chance SNARKs, FHE, and iO Reach Sub-10x

TLDR:

Vitalik Buterin puts the odds of SNARKs, FHE and iO reaching sub-10x computing overhead at 60% overall.
SNARKs are the likeliest to reach single-digit overhead by 2030, but no deadline applies to all three tools.
Buterin assigns a 33% chance that SNARKs, FHE and iO eventually approach 1+ε overhead in real-world use.
Lower-cost SNARKs could support higher Ethereum gas limits without proportional validator hardware increases.

Ethereum co-founder Vitalik Buterin has put numbers around a long-running cryptography question: how close advanced privacy and verification tools are to ordinary computing costs. In a September 6 post, Buterin assigned a 60% probability that SNARKs, FHE and indistinguishability obfuscation eventually operate below 10x computational overhead.
He measured that overhead through total energy use and amortized computing expenses. He also gave all three a 33% chance of approaching 1+ε overhead for average real-world computation.

Vitalik Buterin Sees 60% Chance SNARKs, FHE and iO Reach Sub-10x Overhead
Ethereum co-founder Vitalik Buterin said he believes there is a 60% chance that SNARKs, fully homomorphic encryption and indistinguishability obfuscation could eventually be implemented with single-digit… pic.twitter.com/kdtCcHwajq
— Wu Blockchain (@WuBlockchain) September 6, 2026

That distinction matters as the timeline remains narrower than the headline probability suggests. Buterin did not say all three technologies would cross the sub-10x threshold by 2030. Instead, he said at least one could reach single-digit overhead by decade-end, with SNARKs the most likely candidate.
SNARKs Lead Buterin’s Push Toward Sub-10x Computing Costs
SNARKs allow a system to prove that a computation was performed correctly without requiring every verifier to repeat the entire process. As a result, they have become central to Ethereum’s zero-knowledge scaling model.
Zero-knowledge rollups already use this approach by processing batches of transactions away from Ethereum’s base layer. They then submit validity proofs to Mainnet, allowing the network to verify those transactions while preserving Ethereum’s security guarantees.
However, proof generation remains a major constraint. Complex proofs still require substantial computing power, while some workloads depend on specialized hardware. Even so, Buterin said the efficiency gap is beginning to narrow.
In August, he highlighted research showing that certain large language model inference workloads were approaching less than 10x proving overhead. He also pointed to specialized hash functions, where single-digit overhead has already been achieved.
As proving costs decline, the improvement could have direct implications for Ethereum’s future architecture. The network’s zkEVM roadmap envisions validators verifying proofs of entire blocks instead of independently replaying every transaction.
Consequently, sufficiently efficient proof generation could allow Ethereum to raise gas limits without requiring proportional increases in validator hardware. That would make lower-cost SNARKs increasingly relevant to both scalability and validator efficiency.
FHE and iO Face Higher Barriers to Practical Efficiency
While SNARKs focus on verifying computation, FHE addresses a different challenge: privacy. It allows calculations to run directly on encrypted data without first revealing the underlying information.
NIST describes FHE as a privacy-enhancing technology that can apply arbitrary functions to encrypted data without access to the secret decryption key. For blockchains, that capability could support private automated market makers, confidential lending markets and sealed-bid auctions.
Ethereum’s privacy roadmap identifies these applications directly. However, FHE still carries significantly higher computational costs than ordinary plaintext processing. As a result, reaching sub-10x overhead would represent a major step toward broader practical use.
Indistinguishability obfuscation, or iO, presents an even tougher challenge. The technology aims to transform software while preserving its functionality, making equivalent obfuscated programs computationally indistinguishable.
Although recent research has strengthened iO’s theoretical foundations, its practical costs remain extremely high. Buterin has described traditional constructions as effectively “galactic” in computational expense.
To reduce those costs, his recent work has explored approaches including diamond iO and local mixing. Diamond iO lowers the theoretical burden but remains impractical, while local mixing takes a different route whose security is still unproven.
Even so, each technology targets a distinct part of the broader cryptographic problem. Cheaper SNARKs could make verifiable computation more routine, while FHE could expand private computation across shared data.
Meanwhile, efficient iO could help protect the internal logic of executable software. For now, however, Buterin’s 60% estimate remains a personal probability assessment rather than an Ethereum roadmap commitment.
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