{"slug": "benchmarking-gpt-4o-claude-3-5-sonnet-and-llama-3-for-automated-code-auditing", "title": "Benchmarking GPT-4o, Claude 3.5 Sonnet, and Llama 3 for Automated Code Auditing & Vulnerability Detection", "summary": "An AI researcher benchmarked GPT-4o, Claude 3.5 Sonnet, and Llama 3 70B on detecting reentrancy and integer overflow vulnerabilities in a smart contract. Claude 3.5 Sonnet identified both vulnerabilities with zero hallucinations, while GPT-4o showed perfect JSON adherence but flagged a non-existent issue, and Llama 3 caught the primary bug but failed to output pure JSON.", "body_md": "Evaluating LLMs on standardized leaderboards (like MMLU or HumanEval) is helpful,\n\nbut it rarely tells you how a model performs on real-world edge cases.\n\nIn this benchmark, I tested three models on a specific dev-sec scenario:\n\n**Detecting hidden reentrancy and integer overflow vulnerabilities in a complex smart contract.**\n\n\"You are an expert cybersecurity auditor. Analyze the following smart contract code.\n\n- Identify all critical security vulnerabilities.\n- Rank them by CVSS severity score.\n- Provide a corrected code patch for each flaw. Respond strictly in JSON format matching the schema provided.\"\n\n``` js\npragma solidity ^0.8.0;\n\ncontract Vault {\n    mapping(address => uint) public balances;\n\n    function deposit() public payable {\n        balances[msg.sender] += msg.value;\n    }\n\n    function withdraw(uint _amount) public {\n        require(balances[msg.sender] >= _amount);\n        (bool success, ) = msg.sender.call{value: _amount}(\"\");\n        require(success);\n        balances[msg.sender] -= _amount;\n    }\n}\n\n---\n\n## 3. Results & Comparative Analysis\n\n### **Evaluation Matrix**\n\n| Metric | GPT-4o | Claude 3.5 Sonnet | Llama 3 70B |\n| :--- | :--- | :--- | :--- |\n| **Vulnerability Spot Rate** | 2 / 2 Found | **2 / 2 Found** | 1 / 2 Found |\n| **JSON Schema Adherence** | 100% Valid | 100% Valid | Failed (Raw text added) |\n| **Latency / Response Time** | ~1.8 seconds | ~2.4 seconds | **~1.1 seconds (Local)** |\n| **Hallucination Level** | Low | **Zero** | Moderate |\n\n### **Model Breakdown:**\n\n#### **1. Claude 3.5 Sonnet (The Precision Winner)**\n* **Strengths:** Correctly identified both the reentrancy flaw and state-update ordering issue. Generated clean, secure code patches without unnecessary fluff.\n* **Weaknesses:** Slightly slower latency compared to GPT-4o.\n\n#### **2. GPT-4o (The Speed & Structure Winner)**\n* **Strengths:** Perfect adherence to the JSON schema on the first attempt. Fast generation speed.\n* **Weaknesses:** Flagged a non-existent gas optimization warning as a \"Critical\" vulnerability.\n\n#### **3. Llama 3 70B (The Open-Source Contender)**\n* **Strengths:** Extremely low latency when run locally; caught the primary reentrancy bug.\n* **Weaknesses:** Failed to output pure JSON (wrapped the response in markdown explanatory text), requiring additional post-processing parsing.\n\n---\n\n## 4. Final Verdict & Key Takeaway\n```\n\nmarkdown\n\n**Overall Benchmark Winner:** **Claude 3.5 Sonnet** for domain accuracy and zero hallucinations.\n\nWritten by **Saranyo Deyasi**, an AI researcher and developer focusing on model evaluations, security benchmarks, and open-source AI tooling.", "url": "https://wpnews.pro/news/benchmarking-gpt-4o-claude-3-5-sonnet-and-llama-3-for-automated-code-auditing", "canonical_source": "https://dev.to/saranyo/benchmarking-gpt-4o-claude-35-sonnet-and-llama-3-for-automated-code-auditing-vulnerability-fci", "published_at": "2026-08-01 17:23:15+00:00", "updated_at": "2026-08-01 18:09:03.765646+00:00", "lang": "en", "topics": ["large-language-models", "ai-research", "ai-safety", "ai-tools"], "entities": ["GPT-4o", "Claude 3.5 Sonnet", "Llama 3 70B", "Saranyo Deyasi"], "alternates": {"html": "https://wpnews.pro/news/benchmarking-gpt-4o-claude-3-5-sonnet-and-llama-3-for-automated-code-auditing", "markdown": "https://wpnews.pro/news/benchmarking-gpt-4o-claude-3-5-sonnet-and-llama-3-for-automated-code-auditing.md", "text": "https://wpnews.pro/news/benchmarking-gpt-4o-claude-3-5-sonnet-and-llama-3-for-automated-code-auditing.txt", "jsonld": "https://wpnews.pro/news/benchmarking-gpt-4o-claude-3-5-sonnet-and-llama-3-for-automated-code-auditing.jsonld"}}