OpenAI GPT OSS 20B vs Google Gemini 2.5 Pro

Detailed comparison for LLMs

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On Guardion's LLM vulnerability Benchmark, Google Gemini 2.5 Pro is the more secure of the two: GPT OSS 20B scores 20.0% and Gemini 2.5 Pro scores 16.1% on attack success rate (ASR) (lower is better). One or both scores are estimated from public safety evaluations pending a Guardion benchmark run.

Head-to-Head Overview

Gemini 2.5 Pro is the overall winner in this comparison!

Attack Success Rate (lower is safer)

ASR for OpenAI GPT OSS 20B vs Google Gemini 2.5 Pro. Green marks the safer model on each metric. Only the overall score is available for estimated models.

Overall (ASR)

GPT OSS 20B
20.0%
Gemini 2.5 Pro
16.1%

TAP Attack Method (ASR)

GPT OSS 20B
100.0%
Gemini 2.5 Pro
27.5%

Crescendo Attack Method (ASR)

GPT OSS 20B
100.0%
Gemini 2.5 Pro
19.1%

Zero-Shot (ASR)

GPT OSS 20B
100.0%
Gemini 2.5 Pro
1.6%

Key Highlights

  • Google Gemini 2.5 Pro has a lower Overall (ASR).
  • Google Gemini 2.5 Pro has a lower TAP Attack Method (ASR).
  • Google Gemini 2.5 Pro has a lower Crescendo Attack Method (ASR).
  • Google Gemini 2.5 Pro has a lower Zero-Shot (ASR).

Security Profile

Outward is better on every axis.

OverallTAPCrescendoZero-Shot
GPT OSS 20B
Gemini 2.5 Pro
Full security profile
OpenAI GPT OSS 20B
Full security profile
Google Gemini 2.5 Pro

Frequently asked questions

Is OpenAI GPT OSS 20B or Google Gemini 2.5 Pro more secure?

On Guardion's LLM vulnerability Benchmark, Google Gemini 2.5 Pro is the more secure of the two: GPT OSS 20B scores 20.0% and Gemini 2.5 Pro scores 16.1% on attack success rate (ASR) (lower is better). One or both scores are estimated from public safety evaluations pending a Guardion benchmark run.

What is the attack success rate (ASR) of GPT OSS 20B vs Gemini 2.5 Pro?

GPT OSS 20B has a 20.0% ASR and Gemini 2.5 Pro has a 16.1% ASR — the share of adversarial prompts that succeed across zero-shot, TAP, and Crescendo attacks. Lower is safer.

How were GPT OSS 20B and Gemini 2.5 Pro tested?

Both were red-teamed with the HarmBench framework across zero-shot, TAP (Tree of Attacks with Pruning), and Crescendo multi-turn attacks, scored by Attack Success Rate.

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