# Guardrails AI vs NVIDIA NeMo Guardrails > NVIDIA NeMo Guardrails has a score of 68.7 (B) against Guardrails AI's 49.8 (D). Both do guard injection. The largest gap is maintenance & community, 36 points. Category scores, facts, verdicts and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails - Markdown: https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails.md (~1,650 tokens) - Slim: https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails.min.md (~380 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/guardrails-ai-vs-nemo-guardrails.json (this page as data, same URL with Accept: application/json) - 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: 2026-10-04 NVIDIA NeMo Guardrails has a score of 68.7 (B) against Guardrails AI's 49.8 (D). Both do guard injection. The largest gap is maintenance & community, 36 points. - Guardrails AI: grade D, 49.8/100, rank #366 of 452. Markdown https://www.anchorterminal.com/tools/guardrails-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json - NVIDIA NeMo Guardrails: grade B, 68.7/100, rank #120 of 452. Markdown https://www.anchorterminal.com/tools/nemo-guardrails.md · JSON https://www.anchorterminal.com/api/v1/tools/nemo-guardrails.json ## Which one, for what Pick Guardrails AI for nothing in particular (no category where it leads by five points or more). Pick NVIDIA NeMo Guardrails for reliability (+17), schema & documentation (+10), security & auth (+18), maintenance & community (+36), transparency & trust (+10). ## Score by category | Category | Weight | Guardrails AI | NVIDIA NeMo Guardrails | Edge | | --- | --- | --- | --- | --- | | Reliability | 16% (20 this run) | 58 | 75 | NVIDIA NeMo Guardrails +17 | | Performance | 10%, pending | pending | pending | not scored in this run | | Schema & documentation | 13% (16.2 this run) | 59 | 69 | NVIDIA NeMo Guardrails +10 | | Agent ergonomics | 13% (16.2 this run) | 63 | 67 | NVIDIA NeMo Guardrails +4 | | Security & auth | 14% (17.5 this run) | 44 | 62 | NVIDIA NeMo Guardrails +18 | | Payments & pricing | 10% (12.5 this run) | 60 | 60 | even | | Task success | 10%, pending | pending | pending | not scored in this run | | Maintenance & community | 7% (8.8 this run) | 44 | 80 | NVIDIA NeMo Guardrails +36 | | Transparency & trust | 7% (8.8 this run) | 61 | 71 | NVIDIA NeMo Guardrails +10 | | Negative events | ≤15 | -6 | 0 | | | **Total** | | **49.8 · D** | **68.7 · B** | | ## Facts side by side | Fact | Guardrails AI | NVIDIA NeMo Guardrails | | --- | --- | --- | | Kind | Agent framework | Agent framework | | Vendor | Guardrails AI (Harvey) | NVIDIA | | Hosted endpoint | no (local only) | no (local only) | | Transports | HTTP | HTTP | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | Apache-2.0 | | 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 | 2026-08-14 | 2026-09-16 | | Popularity | 7.3k stars, 81 npm/wk, 32k PyPI/wk | 7.2k stars, 101k PyPI/wk | | Agent reviews | 2/5 (2) | 3/5 (2) | ## Verdicts **Guardrails AI.** Validators have configurable actions for failed checks. Harvey acquired the company on 9 September 2026; the reviewed announcement did not state plans for the library. **NVIDIA NeMo Guardrails.** Apache-2.0, 7,200 stars and nine releases between 9 October 2025 and 16 September 2026. Usage telemetry and a heartbeat every 10 minutes to NVIDIA by default. ## Before you call either ### Guardrails AI 1. Pin guardrails-ai==0.11.0 and each guardrails-ai- package, install only from PyPI, and never install 0.10.1 2. Import validators from guardrails_ai., not guardrails.hub, and don't run guardrails hub install 3. Pass use_local=True to detect_pii, toxic_language and the other model-backed validators, or set validation_endpoint to a server you run 4. Set enable_metrics to false in ~/.guardrailsrc if you don't want usage metrics sent 5. Avoid building on reask and RAIL. The open 1.0.0 issues plan to remove both ### NVIDIA NeMo Guardrails 1. Set NEMO_GUARDRAILS_NO_USAGE_STATS=1 before import unless you want deployment metadata sent to NVIDIA every 10 minutes 2. Use IORails for plain input and output checks. LLMRails and Colang are for dialogue flows a tool-calling agent rarely needs 3. Pin nemoguardrails==0.24.1. 0.24.0 changed message passing to messages= and removed inline config from /v1/checks 4. Call /v1/checks with a config_id loaded on the server and branch on the RailOutcome 5. Put the server behind your own gateway. 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