This data sheet provides a detailed overview of SPLX Platform’s LLM Benchmarks feature – built for CISOs, AI security teams, and technical leaders evaluating which large language models (LLMs) are safe for enterprise use. The feature enables organizations to confidently select and approve models for deployment by providing deep, security-first evaluations across thousands of attack simulations, prompt configurations, and business-critical risk categories.

Make Informed Decisions Before Deploying Any Model

• Access benchmarks of leading LLMs like GPT-4, Claude, Gemini, LLaMA, and Deepseek against real-world threats

• Evaluate security, safety, hallucination rate, and business alignment of each model

• Compare open-source and commercial models side-by-side in a unified view

Understand the Impact of Prompt Engineering on Risk Levels

• Models are stress-tested with no system prompt, a basic system prompt, and a hardened system prompt

• See how prompt configurations dramatically change model behavior and robustness

• Identify which models are safest for agentic apps, assistants, and internal tools

Request Benchmarks of Any Model

• Request any commercial or open-source model for full evaluation

• Access drill-down reports with interaction logs and attack traceability

• Get updated scores as new attack techniques are added to the SplxAI Platform

Take the guesswork out of model selection and reduce the time to secure deployment. Download the data sheet to learn how SPLX’s LLM Benchmarks help organizations confidently choose the right models, mitigate risks, and accelerate AI adoption with trust and clarity.