Google Cloud Model Armor vs ProtectAI LLM Guard

Detailed comparison for runtime guardrails

Google CloudProtectAI

On Guardion's Prompt Attack Risk Benchmark, ProtectAI LLM Guard is the more secure of the two: Model Armor scores NaN% and LLM Guard scores NaN% on F1 score (higher is better).

Head-to-Head Overview

Model Armor is the overall winner in this comparison!

Guardrail Metrics

F1 Score

Model Armor
4.680
LLM Guard
0.000

Accuracy

Model Armor
45.540
LLM Guard
0.000

Precision

Model Armor
76.410
LLM Guard
0.000

Recall

Model Armor
10.670
LLM Guard
0.000

False Positive Rate

Model Armor
4.700
LLM Guard
0.000

False Negative Rate

Model Armor
89.330
LLM Guard
0.000

Average Latency (ms)

Model Armor
0.703
LLM Guard
0.000

p50 Latency (ms)

Model Armor
381.288
LLM Guard
0.000

p90 Latency (ms)

Model Armor
1549.410
LLM Guard
0.000

Key Highlights

  • Google Cloud Model Armor has a better F1 Score.
  • Google Cloud Model Armor has a better Accuracy.
  • Google Cloud Model Armor has a better Precision.
  • Google Cloud Model Armor has a better Recall.
  • ProtectAI LLM Guard has a better False Positive Rate.
  • ProtectAI LLM Guard has a better False Negative Rate.
  • ProtectAI LLM Guard has a better Average Latency (ms).
  • ProtectAI LLM Guard has a better p50 Latency (ms).
  • ProtectAI LLM Guard has a better p90 Latency (ms).

Security Profile

Outward is better on every axis.

F1 ScoreAccuracyPrecisionRecallFPRFNRAverage Latency (ms)p50 Latency (ms)p90 Latency (ms)
Model Armor
LLM Guard
Full security profile
Google Cloud Model Armor
Full security profile
ProtectAI LLM Guard

Frequently asked questions

Is Google Cloud Model Armor or ProtectAI LLM Guard more secure?

On Guardion's Prompt Attack Risk Benchmark, ProtectAI LLM Guard is the more secure of the two: Model Armor scores NaN% and LLM Guard scores NaN% on F1 score (higher is better).

What is the F1 score of Model Armor vs LLM Guard?

Model Armor scores NaN% F1 and LLM Guard scores NaN% F1 on Guardion's prompt-attack benchmark. F1 balances precision and recall — higher is better.

How were Model Armor and LLM Guard tested?

Both were evaluated via API at production-like sensitivity against 30+ prompt-attack categories using zero-shot, Crescendo, and TAP methods, scored by F1.

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