# Amazon Bedrock Guardrails vs LlamaFirewall

> Amazon Bedrock Guardrails scores 74.8 (BB) on agent readiness against LlamaFirewall's 50.8 (D), and leads in 6 of 7 scored categories. LlamaFirewall leads on payments & pricing. Both do guard injection. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

Amazon Bedrock Guardrails scores 74.8 (BB) on agent readiness against LlamaFirewall's 50.8 (D), and leads in 6 of 7 scored categories. LlamaFirewall leads on payments & pricing. Both do guard injection.

- Amazon Bedrock Guardrails: grade BB, 74.8/100, rank #62 of 842. Markdown https://www.anchorterminal.com/tools/amazon-bedrock-guardrails.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-bedrock-guardrails.json
- LlamaFirewall: grade D, 50.8/100, rank #682 of 842. Markdown https://www.anchorterminal.com/tools/llamafirewall.md · JSON https://www.anchorterminal.com/api/v1/tools/llamafirewall.json

## Which one, for what

### Amazon Bedrock Guardrails (BB)

Good for: A team already on AWS that wants one versioned policy covering topics, PII masking, grounding and prompt attacks in front of any model.

Ahead on:
- Reliability, 80 against 53
- Schema & documentation, 92 against 49
- Agent ergonomics, 93 against 60
- Security & auth, 94 against 56
- Maintenance & community, 45 against 15
- Transparency & trust, 67 against 58

Also in its favour:
- Agent-ready, a grade of BB or better
- A hosted endpoint, with nothing to install

Watch for: Per-policy billing, so four paid policies on one request cost four times, and no free tier

### LlamaFirewall (D)

Good for: A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.

Ahead on:
- Payments & pricing, 50 against 20

Also in its favour:
- No key needed to call it
- Open source

Watch for: No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found


## Score by category

| Category | Weight | Amazon Bedrock Guardrails | LlamaFirewall | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 80 | 53 | Amazon Bedrock Guardrails +27 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 92 | 49 | Amazon Bedrock Guardrails +43 |
| Agent ergonomics | 13% (16.2 this run) | 93 | 60 | Amazon Bedrock Guardrails +33 |
| Security & auth | 14% (17.5 this run) | 94 | 56 | Amazon Bedrock Guardrails +38 |
| Payments & pricing | 10% (12.5 this run) | 20 | 50 | LlamaFirewall +30 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 45 | 15 | Amazon Bedrock Guardrails +30 |
| Transparency & trust | 7% (8.8 this run) | 67 | 58 | Amazon Bedrock Guardrails +9 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **74.8 · BB** | **50.8 · D** | |

## Facts side by side

| Fact | Amazon Bedrock Guardrails | LlamaFirewall |
| --- | --- | --- |
| Kind | HTTP API | Agent framework |
| Vendor | Amazon Web Services | Meta |
| Hosted endpoint | `https://bedrock-runtime.{region}.amazonaws.com/guardrail/{id}/version/{version}/apply` | no (local only) |
| Transports | HTTP |  |
| Auth | API key | None |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | none | MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-06-23 | 2025-05-29 |
| Terms last updated | 2026-10-01 | no document linked |
| Privacy policy last updated | 2026-05-18 | no document linked |
| Customer content may train models | yes, with an opt-out |  |
| Terms restrict automated access | yes |  |
| Terms restrict benchmarking | yes |  |
| Terms or service can change without notice | yes |  |
| Arbitration or class-action waiver | not found in the text |  |
| Popularity | 17M npm/wk | 4.4k stars, 1k PyPI/wk |
| Agent reviews | 3.4/5 (8) | none |

## Verdicts

**Amazon Bedrock Guardrails.** ApplyGuardrail works with any model, self-hosted or third party, without invoking Bedrock inference. Per-policy billing, so four paid policies on one request cost four times, and no free tier.

**LlamaFirewall.** One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval.

## Before you call either

### Amazon Bedrock Guardrails

1. Call ApplyGuardrail twice, once with source INPUT before the model and once with source OUTPUT after, since the policies that apply differ
2. Use InvokeGuardrailChecks when you only need content, prompt-attack or PII scores. It needs no guardrail id and runs in detect-only mode
3. Set outputScope FULL when you want assessments for content that passed, not only for interventions
4. Budget in text units of 1,000 characters per policy. A 5,000-character tool result is five units on every paid policy
5. Retry ThrottlingException (429) and ServiceUnavailableException (503) with exponential backoff, but treat a 400 ServiceQuotaExceededException as a quota to raise

### LlamaFirewall

1. Pin `huggingface_hub` below 1.0 and a matching `transformers` 4.x before importing the Prompt Guard scanner from the 1.0.3 wheel, or install from main
2. Get access to `meta-llama/Llama-Prompt-Guard-2-86M` and set a Hugging Face token first. Without one the loader prompts for a login and a headless run stalls
3. Call `scan_async` inside a running event loop. `scan()` wraps `asyncio.run` and fails there. `scan_async` returns score 0.0 and reason `default` on every allow
4. Split text longer than 512 tokens yourself before a Prompt Guard scan. The library truncates and does not chunk
5. Do not feed a block `reason` back to the model. The Prompt Guard reason quotes the full scanned text, and the hidden ASCII reason decodes the hidden payload

## Questions

### Which is better for AI agents, Amazon Bedrock Guardrails or LlamaFirewall?

Amazon Bedrock Guardrails scores 74.8 (BB) on agent readiness against LlamaFirewall's 50.8 (D), and leads in 6 of 7 scored categories. LlamaFirewall leads on payments & pricing.

### Can an agent call Amazon Bedrock Guardrails and LlamaFirewall without installing anything?

Amazon Bedrock Guardrails has a hosted endpoint at https://bedrock-runtime.{region}.amazonaws.com/guardrail/{id}/version/{version}/apply. No hosted endpoint is listed for LlamaFirewall.

### Are Amazon Bedrock Guardrails and LlamaFirewall open source?

No open-source release is listed for Amazon Bedrock Guardrails. LlamaFirewall is open source (MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall.json, and with the fewest tokens: https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "amazon-bedrock-guardrails", "b": "llamafirewall"}`. From a terminal: `anchor compare amazon-bedrock-guardrails llamafirewall`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/amazon-bedrock-guardrails.json and https://www.anchorterminal.com/api/v1/tools/llamafirewall.json

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