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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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ChainBench: An LLM Benchmark for Cross-Chain Code Generation

Authors: Swair Shah; Austin Bennett; Madelyn Scandlen;

ChainBench: An LLM Benchmark for Cross-Chain Code Generation

Abstract

AI agents are increasingly capable of repository scale software work, and smart-contract engineering is a particularly high-stakes setting where toolchains and tests enforce correctness. We introduce ChainBench, a benchmark for cross-chain smart contract translation and contract generation built from production repositories and their real verification suites. Each task provides a structured specification and containerized environment: systems implement missing functionality to pass the existing verification suite, and are scored by Pass@1 task success. ChainBench contains 42 tasks spanning EVM Solidity, NEAR Rust, Aptos Move, Sui Move, and Starknet Cairo. In a zero-shot evaluation of nine deployed model-agent systems, including both standardized same harness runs and preferred-harness runs where available, the best achieves 88.1% success, while several open-weight systems reach 52%–60% with substantially longer solve times. Performance further varies by target chain and task type, with failures ranging from narrow behavioral mismatches (e.g., missing edge case guards) to build and repository-compatibility issues.

Keywords

LLM, Cryptocurrencies, Smart Contract, Blockchain, Blockchain AI, Benchmark, LLM Benchmark, Code Generation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green