Google Cloud Model Armor vs Lakera Guard (Check Point AI Guardrails)

Google Cloud Model Armor

2 million free tokens a month, then $0.10 per million. OAuth only, and a template must exist in the same location as the endpoint before the first call.

Lakera Guard (Check Point AI Guardrails)

OpenAI message format in, including tools, tool calls and tool results. Prompts and outputs are stored for the dashboard by default.

Google Cloud Model Armor

1. Create one template per location you call from. A template in us-central1 doesn't answer on the europe-west2 endpoint
2. Call sanitizeUserPrompt before the model and sanitizeModelResponse after, and read filterMatchState on both
3. Treat EXECUTION_SKIPPED as unchecked, not clean. It means the input went over the filter's 65,536-token cap
4. Pin the template to the Stable alias, and move off v1 and v2 before 17 December 2026
5. Retry 500, 502, 503 and 504 with truncated exponential backoff, and keep fan-out under the 1,200 queries a minute shared by the project

Lakera Guard (Check Point AI Guardrails)

1. Start the project in Detect mode and calibrate before Enforce. In Detect mode flagged is always false
2. Send the whole conversation, but expect only the last user, assistant or tool turn to be scored
3. Ask for breakdown=true and treat the confidence levels as a dial, not a boolean
4. Turn off prompt logging in General Settings if the dashboard shouldn't hold user content
5. Pin eu.api.lakera.ai or us.api.lakera.ai rather than api.lakera.ai when residency matters