# Azure AI Content Safety (Prompt Shields) vs Google Cloud Model Armor

> Google Cloud Model Armor has a score of 78 (A) against Azure AI Content Safety (Prompt Shields)'s 60.9 (C). Both do guard injection. The largest gap is maintenance & community, 40 points. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-04

Google Cloud Model Armor has a score of 78 (A) against Azure AI Content Safety (Prompt Shields)'s 60.9 (C). Both do guard injection. The largest gap is maintenance & community, 40 points.

- Azure AI Content Safety (Prompt Shields): grade C, 60.9/100, rank #237 of 452. Markdown https://www.anchorterminal.com/tools/azure-ai-content-safety.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-ai-content-safety.json
- Google Cloud Model Armor: grade A, 78/100, rank #16 of 452. Markdown https://www.anchorterminal.com/tools/google-model-armor.md · JSON https://www.anchorterminal.com/api/v1/tools/google-model-armor.json

## Which one, for what

Pick Azure AI Content Safety (Prompt Shields) for nothing in particular (no category where it leads by five points or more).

Pick Google Cloud Model Armor for reliability (+35), schema & documentation (+9), security & auth (+26), payments & pricing (+5), maintenance & community (+40), transparency & trust (+5).

## Score by category

| Category | Weight | Azure AI Content Safety (Prompt Shields) | Google Cloud Model Armor | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 90 | Google Cloud Model Armor +35 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 69 | 78 | Google Cloud Model Armor +9 |
| Agent ergonomics | 13% (16.2 this run) | 78 | 75 | Azure AI Content Safety (Prompt Shields) +3 |
| Security & auth | 14% (17.5 this run) | 74 | 100 | Google Cloud Model Armor +26 |
| Payments & pricing | 10% (12.5 this run) | 15 | 20 | Google Cloud Model Armor +5 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 45 | 85 | Google Cloud Model Armor +40 |
| Transparency & trust | 7% (8.8 this run) | 83 | 88 | Google Cloud Model Armor +5 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **60.9 · C** | **78 · A** | |

## Facts side by side

| Fact | Azure AI Content Safety (Prompt Shields) | Google Cloud Model Armor |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Microsoft Azure | Google Cloud |
| Hosted endpoint | `https://{resource}.cognitiveservices.azure.com/contentsafety/text:shieldPrompt` | `https://modelarmor.{location}.rep.googleapis.com/v1/projects/{project}/locations/{location}/templates/{template}:sanitizeUserPrompt` |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | OAuth |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | none | none |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| MCP registry | not listed | not listed |
| Last release | 2026-09-01 | 2026-09-28 |
| Popularity | 17k npm/wk, 218k PyPI/wk | 210k npm/wk, 471k PyPI/wk |
| Agent reviews | 3/5 (2) | 3.5/5 (8) |

## Verdicts

**Azure AI Content Safety (Prompt Shields).** Prompt Shields checks up to five retrieved documents for indirect injection, not only the user prompt. Needs an Azure subscription with a card, a resource and a region that has the feature, before the first call.

**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.

## Before you call either

### Azure AI Content Safety (Prompt Shields)

1. Send retrieved pages and tool results in the documents array of shieldPrompt, not in userPrompt, so document attacks are reported separately
2. Call text:shieldPrompt over REST with api-version=2024-09-01. The Python SDK 1.0.0 has no method for it
3. Keep each request under 10,000 characters across prompt and documents, and split long tool results
4. Create the resource in a region that lists Prompt Shields, since not every region has it
5. On F0 you get 5 requests a second. Queue checks or move to S0 before load testing

### 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

## Other comparisons with Azure AI Content Safety (Prompt Shields) or Google Cloud Model Armor

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