Solidity LLM is a specialized Large Language Model (LLM) developed by ChainGPT, finely tuned to efficiently generate, understand, and analyze Solidity smart contracts. Designed explicitly for the decentralized development ecosystem, Solidity LLM delivers exceptional results, significantly outperforming larger models in syntax accuracy (~83% compilation success), gas optimization (~72% efficiency), and adherence to established standards (~65% OpenZeppelin compliance). By using Solidity LLM, developers achieve faster development cycles, reduced debugging time, and substantial cost savings.
Model Type: Causal Language Model (Code Generation)
Tokenizer: GPT2Tokenizer
Parameters: 2 Billion
Transformer Layers: 32
Solidity LLM was benchmarked against leading LLMs (GPT-4.5 Preview, GPT-4o mini, Qwen 2.5-Coder-7B, DeepSeek-Coder-7B). Key metrics included:
These benchmarks reflect Solidity LLM’s exceptional efficiency, accuracy, and cost-effectiveness.
Smart contract development assistance
Solidity educational resources
Documentation and template creation
Integrated Development Environments (IDEs)
Autonomous blockchain agents
General-purpose coding (other languages)
Legal auditing or formal verification without human oversight
Production deployment without manual review
Possible biases from training datasets
Occasional hallucinations or logically incorrect outputs
Caution required in financial or high-stakes scenarios
Recommendation: Always conduct manual code reviews and thorough testing before deploying generated code.
Compute Resources: 80 GB GPU cluster (4 GPUs)
Training Duration: ~1095 hours (1.5 months)
Pre-training: 1 billion tokens of raw Solidity data
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Feature
Timeline
HuggingFace:
Solidity LLM by ChainGPT empowers Web3 developers with a reliable, high-performance model explicitly crafted for Solidity smart contract generation, combining robust technical performance with tangible business impact.