cybersecurity
Best LLM for Vulnerability Review
Compare models for reviewing code for security vulnerabilities and proposing mitigations.
#1 Recommendation
gemini-2.5-pro
Strong on VADER Leaderboard mean_score_pct (81%) and BaxBench Leaderboard average_secure_pass_1_pct (44%)
external/google/gemini-2-5-pro
21.2%
Score
32.1%
Confidence
23
Evidence
Ranked Models
30
Evidence Quality
80%
Scoring
Benchmark-backed
Top Signal
VADER Leaderboard: mean_score_pct
All Ranked Models
| Rank | Model | Score |
|---|---|---|
| #1 | gemini-2.5-pro Strong on VADER Leaderboard mean_score_pct (81%) and BaxBench Leaderboard average_secure_pass_1_pct (44%) | 21.2% |
| #4 | Meta-Llama-3-8B-Instruct | 16.0% |
| #5 | gpt-4o-2024-05-13 | 15.8% |
| #6 | Llama-2-7b-chat-hf | 15.1% |
| #8 | openai/gpt-4o-mini-2024-07-18 | 13.1% |
| #9 | deepseek/deepseek-r1 | 13.1% |
| #10 | gpt-4.1-20250414 | 12.5% |
| #11 | Kimi K2 Thinking | 12.2% |
| #12 | gemma-7b-it | 12.2% |
| #13 | gemma-2b-it | 12.2% |
| #15 | z-ai/glm-4.7 | 11.9% |
| #17 | falcon-7b-instruct | 11.3% |
| #19 | minimax/minimax-m2.1 | 11.2% |
| #21 | gemini-3-pro-preview | 10.8% |
| #23 | zephyr-7b-beta | 10.4% |
| #25 | GLM-5 | 10.4% |
| #28 | Grok-4-0709 | 10.2% |
| #29 | claude-sonnet-4-20250514 | 9.8% |
| #30 | google/gemini-3.1-pro-preview | 9.8% |
| #32 | gpt-5-2025-08-07 | 9.0% |
| #33 | openai/gpt-5.4-2026-03-05 | 8.9% |
| #34 | gpt-4o | 8.8% |
| #35 | gpt-5.1-2025-11-13 | 8.6% |
| #36 | anthropic/claude-sonnet-4.6 | 8.6% |
| #37 | claude-opus-4-5-20251101 | 8.5% |
| #38 | gpt-5-mini-2025-08-07 | 8.3% |
| #39 | gemini-3-flash-preview | 8.1% |
| #40 | alpaca-native | 8.1% |
| #41 | x-ai/grok-3 | 8.0% |
| #42 | Mistral-7B-OpenOrca | 8.0% |
Head-to-Head: #1 vs #2
#1
Top Pickgemini-2.5-pro
Strong on VADER Leaderboard mean_score_pct (81%) and BaxBench Leaderboard average_secure_pass_1_pct (44%)
Conf 32.1%
#4
Meta-Llama-3-8B-Instruct
Strong on LLM Trustworthy Leaderboard adv (100%) and LLM Trustworthy Leaderboard privacy (69%)
Conf 24.2%
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