Lakera vs LLM Guard
A side-by-side comparison of Lakera and LLM Guard, two Security tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
LLM Guard
SecuritySecurity toolkit that sanitizes and screens LLM prompts and responses.
View LLM GuardAt a glance
| Attribute | Lakera | LLM Guard |
|---|---|---|
| Category | Security | Security |
| Pricing (differs) | FREEMIUM | FREE |
| License (differs) | Proprietary | Open source |
| Deployment (differs) | Hybrid | — |
| Platforms (differs) | API, Web | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Lakera (Check Point) | Protect AI (Palo Alto Networks) |
The honest brief
Lakera
Detection models trained on 80M+ real adversarial prompts from its viral Gandalf game; sub-50ms inline latency.
- Detection sharpened by the Gandalf game
- Low sub-50ms latency, inline-friendly
- Covers injection, jailbreaks, PII, data loss
- Model-agnostic API in front of any LLM
- Behavioral detection risks false positives
- Core product is closed source
- Enterprise pricing quoted by sales
LLM Guard
Runs entirely self-hosted and free, with composable input and output scanners — no per-call cost or sending prompts to a hosted guardrail API.
- Prompt-injection & jailbreak detection
- PII redaction and secrets scanning
- Composable input/output scanners
- Self-hosted — data stays in your stack
- Active community, well-documented
- Python library — you build the integration
- No managed/hosted option
- Latency from running multiple scanners
- Tuning needed to cut false positives