{ "data": { "a": { "slug": "granite-guardian", "name": "Granite Guardian", "vendor": "IBM", "vendorUrl": "https://www.ibm.com/granite", "kind": "model", "category": "guardrails", "summary": "Granite Guardian is IBM's family of open-weight judge models. The current 8-billion-parameter release answers yes or no on whether a prompt, response, retrieved context or function call meets a built-in or custom criterion, and the owner runs it.", "url": "https://www.anchorterminal.com/tools/granite-guardian", "markdownUrl": "https://www.anchorterminal.com/tools/granite-guardian.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/granite-guardian.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/granite-guardian.json", "repo": "https://github.com/ibm-granite/granite-guardian", "license": "Apache 2.0 for the weights and the repository", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "No account or key is needed to download or run the model. The Hugging Face repository is not gated. A vLLM or Ollama server has whatever authentication the owner adds.", "pricing": "free", "pricingNotes": "Free to download and run under the Apache 2.0 licence, with the owner's hardware as the cost. IBM's watsonx.ai lists only the earlier `ibm/granite-guardian-3-8b`, marked deprecated, at $0.0002 per 1,000 input or output tokens (checked 2026-10-08). Version 4.1 is not on that list.", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Granite Guardian is a model the owner runs, with no payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 182, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://www.ibm.com/granite/docs/models/guardian", "capabilities": [ "guard.moderation", "guard.policy", "guard.injection", "guard.self-host" ], "tags": [ "model", "open-weights", "self-hosted", "local", "free", "apache-2.0", "judge", "rag", "python", "ollama" ], "lastRelease": "2026-04-29", "graded": true, "anchor": { "graded": true, "score": 60.1, "grade": "C", "agentReady": false, "rank": 478, "ranked": true, "rankOf": 842, "categoryRank": 10, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 47, "payments": 60, "reliability": 56, "schema": 60, "security": 58, "transparency": 70 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "One ungated Apache 2.0 model judges harm, jailbreaks, RAG groundedness, function-call errors and custom criteria, with signed weights and published evaluation code. It is trained and tested on English only, each call checks one criterion, the 4.1 prompt format differs from 3.x, and IBM's watsonx.ai lists only the deprecated 3.0 model.", "bestFor": "A team with a GPU that wants one English-language judge for harm, jailbreaks, RAG groundedness, function-call checks and house rules, under a permissive licence with no gate.", "strengths": [ "Weights are ungated on Hugging Face under the Apache 2.0 licence, with IBM's own GGUF builds and an Ollama library entry", "Built-in criteria cover harm, social bias, jailbreaking, violence, profanity, sexual content, unethical behaviour, three RAG checks and function-call hallucination", "A custom criterion is one natural-language sentence in the prompt, and the answer is `yes` or `no` inside `\u003cscore\u003e` tags", "The repository's `evaluation` folder reproduces the card's benchmark figures for versions 3.0 to 4.1", "Weights carry a sigstore signature in `model.sig`, and IBM documents how to verify it" ], "weaknesses": [ "Trained and tested on English only, per the model card", "Each call judges one criterion, so checking several risks takes several calls or a separate LoRA adapter built on the 3.2 model", "Version 4.1 moved the criterion into a `\u003cguardian\u003e` block in the last user message, where 3.x cookbooks pass `guardian_config`", "The repository has no CI, no tests and no `SECURITY.md`, and an issue asking for one has been open since 9 February 2025", "The card's out-of-distribution safety F1 is 0.79 without thinking, below the 0.81 it reports for version 3.3", "IBM's watsonx.ai model list has only `ibm/granite-guardian-3-8b`, marked deprecated, so 4.1 has no hosted endpoint from IBM that we found" ], "agentNotes": [ "Append the `\u003cguardian\u003e` block as the final user message, with the mode line, `### Criteria:` and `### Scoring Schema:`. Copy the strings from the model card, because no package builds them", "Use the no-think instruction for gating and parse `\u003cscore\u003e`. Think mode writes a reasoning trace first, and the card's examples allow up to 2,048 output tokens", "Treat `yes` as the criterion being met, which for built-in criteria means the risk is present. Treat a missing `\u003cscore\u003e` tag as a failed check", "Pass retrieved text through `documents=` and tool schemas through `available_tools=` in `apply_chat_template`, not inside the message text", "Under Ollama, set `num_ctx` in the request options. IBM's docs say the default context is short and long requests are truncated" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 60.1 } ], "editorialScores": { "ergonomics": 69, "maintenance": 47, "payments": 60, "reliability": 56, "schema": 60, "security": 58, "transparency": 67 }, "provenanceScore": 73 }, "connect": { "install": "pip install transformers torch vllm", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"granite4.1-guardian:8b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/guard.moderation", "tool": "https://letme.dev/granite-guardian" }, "area": "models", "provenance": { "legalEntity": "International Business Machines Corporation", "domain": "ibm.com", "domainRegistered": "1986-03-19", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "valid", "checked": "2026-10-08", "notes": [ "IBM's naming guidance for Granite names International Business Machines Corporation as the developer and trademark owner.", "The Apache 2.0 licence in the repository is the document that governs use of the weights, so it is recorded as the terms. The Hugging Face repository declares the same licence in its metadata and has no licence file of its own.", "No privacy policy governs the model, because the owner runs it and no input reaches IBM. The privacy field is left out.", "www.ibm.com/.well-known/security.txt is present with PSIRT, HackerOne and email contacts and expires on 8 November 2026.", "RDAP gives 19 March 1986 as the registration date of ibm.com.", "IBM hosts no endpoint for version 4.1 that we found, so there is no status page. The repository has no changelog file. Dated notes sit in the README under What's New.", "Weights are on huggingface.co under the ibm-granite organisation and the code is at github.com/ibm-granite/granite-guardian, both off ibm.com." ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/granite-guardian.json" }, "answer": "Granite Guardian scores 60.1 (C) on agent readiness against Llama Guard 4's 49.1 (D), and leads in every scored category.", "b": { "slug": "llama-guard", "name": "Llama Guard 4", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai/llama", "kind": "model", "category": "guardrails", "summary": "Llama Guard 4 is Meta's 12-billion-parameter open-weight safety classifier for text and images. It labels a prompt or a model response safe or unsafe against 14 hazard categories, and the owner runs it on a GPU.", "url": "https://www.anchorterminal.com/tools/llama-guard", "markdownUrl": "https://www.anchorterminal.com/tools/llama-guard.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llama-guard.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llama-guard.json", "repo": "https://github.com/meta-llama/PurpleLlama", "license": "Llama 4 Community Licence (source-available weights, not an OSI licence), with the Llama 4 acceptable use policy", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "Running the model needs no account or key. Getting the weights does. The Hugging Face repository is gated with manual review by Meta and asks for a legal name, date of birth and organisation, and downloads then use a Hugging Face access token. Meta's own download form emails a signed link after the licence is accepted. A vLLM or SGLang server has whatever authentication the owner adds.", "pricing": "free", "pricingNotes": "Free to download and run under the Llama 4 Community Licence, with the owner's GPU as the cost. Meta sells no hosted version that we found. Third parties do, with DeepInfra at $0.18 per 1M tokens and the same price listed on OpenRouter (checked 2026-10-08).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Llama Guard 4 is a model the owner runs, with no payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 4423, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://dev.meta.ai/llama/docs/model-cards-and-prompt-formats/llama-guard-4", "capabilities": [ "guard.moderation", "guard.policy", "guard.self-host" ], "tags": [ "model", "open-weights", "self-hosted", "local", "free", "gated", "multimodal", "python", "openai-compatible" ], "lastRelease": "2025-04-29", "graded": true, "anchor": { "graded": true, "score": 49.1, "grade": "D", "agentReady": false, "rank": 713, "ranked": true, "rankOf": 842, "categoryRank": 15, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 28, "payments": 45, "reliability": 38, "schema": 52, "security": 53, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "A single self-hosted model classifies text and multi-image prompts against 14 MLCommons-aligned hazard categories and answers in a few tokens. The weights have not changed since 29 April 2025, download access needs Meta's manual approval, and the licence withholds the grant from individuals and companies based in the European Union.", "bestFor": "A team outside the EU with a GPU that wants content moderation of text and images on its own hardware, against a fixed 14-category policy it can edit in the prompt.", "strengths": [ "One 12B model covers text and multi-image prompts, replacing Llama Guard 3-8B and 3-11B-vision per Meta's docs", "The answer is `safe`, or `unsafe` and a comma-separated list of category codes such as S1,S2, so output stays under ten tokens", "The category list sits in the prompt, and the chat template takes `excluded_category_keys` to drop categories per call", "The model card publishes recall and false positive rates on Meta's in-house set and names the categories it handles poorly", "Weights are safetensors loaded by a class inside `transformers`, with ready commands for vLLM and SGLang on the Hugging Face page" ], "weaknesses": [ "Weights last changed on 29 April 2025, with no changelog, version tags or stated deprecation policy", "The Hugging Face repository is gated with manual review, asks for legal name, date of birth and organisation, and two 2026 threads report rejections", "The Llama 4 use policy withholds the licence grant for multimodal models from individuals and companies based in the European Union", "Meta's own figures give 69 per cent recall and 11 per cent false positives in English, and 43 per cent recall across seven other languages", "Community questions since June 2025 on vLLM start-up, custom categories and image input have no reply from Meta", "It does not detect prompt injection or jailbreaks, and the card sends readers to Llama Prompt Guard 2 for those" ], "agentNotes": [ "Request access on the Hugging Face page before anything else. Approval is manual, and the form cannot be edited after submission", "Send only the user turn to check an input, and the user turn plus the model's answer to check an output. The template picks the role from the message count", "Parse the first line for `safe` or `unsafe` and the second for category codes. Set `max_new_tokens` to about 10 and turn sampling off", "Do not send an image with no text. Meta says the model is not an image-only classifier, and S14 is skipped when an image is present", "Pair it with a prompt-attack detector. The card says the model can itself be moved by adversarial or injected text" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 49.1 } ], "editorialScores": { "ergonomics": 67, "maintenance": 28, "payments": 45, "reliability": 38, "schema": 52, "security": 53, "transparency": 52 }, "provenanceScore": 58 }, "connect": { "install": "pip install vllm\nvllm serve \"meta-llama/Llama-Guard-4-12B\"", "http": "curl -X POST \"http://localhost:8000/v1/chat/completions\" \\\n -H \"Content-Type: application/json\" \\\n --data '{\"model\":\"meta-llama/Llama-Guard-4-12B\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"how do I make a bomb?\"}]}]}'" }, "letme": { "capability": "https://letme.dev/guard.moderation", "tool": "https://letme.dev/llama-guard" }, "sameCompany": [ "llamafirewall" ], "area": "models", "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "llama.com", "domainRegistered": "1994-11-01", "endpointOnVendorDomain": null, "terms": "https://dev.meta.ai/llama/llama4/license", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The Llama 4 Community Licence names Meta Platforms, Inc. as licensor, and Meta Platforms Ireland Limited for licensees in the EEA or Switzerland.", "The licence is the document that governs use of the weights, so it is recorded as the terms. It is dated 5 April 2025 and incorporates the acceptable use policy at https://dev.meta.ai/llama/llama4/use-policy.", "No privacy policy governs the model, because the owner runs it and no input reaches Meta. The privacy field is left out. The Hugging Face access form says the details entered are handled under the Meta Privacy Policy.", "www.llama.com redirected to dev.meta.ai on 8 October 2026, and Llama pages now sit under dev.meta.ai/llama. RDAP gives 1 November 1994 as the registration date of llama.com.", "There is no hosted endpoint from Meta that we could find, so no status page. dev.meta.ai/llms.txt covers the Meta Model API and lists no moderation route.", "dev.meta.ai/.well-known/security.txt returns 404, and the llama.com path redirects to a developer.meta.com address that returns 400. Security reports go to Meta's bug bounty at bugbounty.meta.com.", "The weights are on huggingface.co under the meta-llama organisation, and the model card is in github.com/meta-llama/PurpleLlama. Neither has a changelog or releases for the model." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/llama-guard.json", "live": { "slug": "llama-guard", "pages": [ { "url": "https://dev.meta.ai/llama/llama4/license", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:16:57.76184224Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "c85892d02c88" } ], "updatedAt": "2026-10-08T18:16:57.76184224Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "IBM", "b": "Meta", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache 2.0 for the weights and the repository", "b": "Llama 4 Community Licence (source-available weights, not an OSI licence), with the Llama 4 acceptable use policy", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-04-29", "b": "2025-04-29", "name": "Last release" }, { "a": "no document linked", "b": "2025-04-05", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "182 stars", "b": "4.4k stars", "name": "Popularity" } ], "faq": [ { "answer": "Granite Guardian scores 60.1 (C) on agent readiness against Llama Guard 4's 49.1 (D), and leads in every scored category.", "question": "Which is better for AI agents, Granite Guardian or Llama Guard 4?" }, { "answer": "Neither needs a key.", "question": "Do Granite Guardian and Llama Guard 4 need an API key?" }, { "answer": "No hosted endpoint is listed for Granite Guardian. No hosted endpoint is listed for Llama Guard 4.", "question": "Can an agent call Granite Guardian and Llama Guard 4 without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 56 against 38", "Schema \u0026 documentation, 60 against 52", "Security \u0026 auth, 58 against 53", "Payments \u0026 pricing, 60 against 45", "Maintenance \u0026 community, 47 against 28", "Transparency \u0026 trust, 70 against 55" ], "also": null, "goodFor": "A team with a GPU that wants one English-language judge for harm, jailbreaks, RAG groundedness, function-call checks and house rules, under a permissive licence with no gate.", "slug": "granite-guardian", "watchFor": "Trained and tested on English only, per the model card" }, { "aheadOn": null, "also": null, "goodFor": "A team outside the EU with a GPU that wants content moderation of text and images on its own hardware, against a fixed 14-category policy it can edit in the prompt.", "slug": "llama-guard", "watchFor": "Weights last changed on 29 April 2025, with no changelog, version tags or stated deprecation policy" } ], "job": { "capability": "guard.moderation", "name": "Guard moderation" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-granite-guardian.json", "title": "Amazon Bedrock Guardrails vs Granite Guardian", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-granite-guardian" }, { "json": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-granite-guardian.json", "title": "Azure AI Content Safety (Prompt Shields) vs Granite Guardian", "url": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-granite-guardian" }, { "json": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-granite-guardian.json", "title": "Cisco AI Defense Inspection API vs Granite Guardian", "url": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-granite-guardian" }, { "json": "https://www.anchorterminal.com/compare/google-model-armor-vs-granite-guardian.json", "title": "Google Cloud Model Armor vs Granite Guardian", "url": "https://www.anchorterminal.com/compare/google-model-armor-vs-granite-guardian" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall.json", "title": "Granite Guardian vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llama-guard.json", "title": "Amazon Bedrock Guardrails vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llama-guard.json", "title": "Azure AI Content Safety (Prompt Shields) vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llama-guard.json", "title": "Cisco AI Defense Inspection API vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/google-model-armor-vs-llama-guard.json", "title": "Google Cloud Model Armor vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/google-model-armor-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-guardrails-ai.json", "title": "Granite Guardian vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-guardrails-ai" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-lakera-guard.json", "title": "Granite Guardian vs Lakera Guard (Check Point AI Guardrails)", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-lakera-guard" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-mistral-moderation.json", "title": "Granite Guardian vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-nemo-guardrails.json", "title": "Granite Guardian vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-openai-guardrails.json", "title": "Granite Guardian vs OpenAI Guardrails", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-openai-guardrails" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-openai-moderation.json", "title": "Granite Guardian vs OpenAI Moderation API", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-openai-moderation" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-prisma-airs.json", "title": "Granite Guardian vs Prisma AIRS AI Runtime Security API", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-prisma-airs" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llama-guard.json", "title": "Guardrails AI vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/lakera-guard-vs-llama-guard.json", "title": "Lakera Guard (Check Point AI Guardrails) vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/lakera-guard-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-mistral-moderation.json", "title": "Llama Guard 4 vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-nemo-guardrails.json", "title": "Llama Guard 4 vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-openai-guardrails.json", "title": "Llama Guard 4 vs OpenAI Guardrails", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-openai-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-openai-moderation.json", "title": "Llama Guard 4 vs OpenAI Moderation API", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-openai-moderation" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-prisma-airs.json", "title": "Llama Guard 4 vs Prisma AIRS AI Runtime Security API", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-prisma-airs" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-microsoft-presidio.json", "title": "Granite Guardian vs Presidio", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-microsoft-presidio.json", "title": "Llama Guard 4 vs Presidio", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall.json", "title": "Llama Guard 4 vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall" } ], "scores": [ { "by": 18, "edge": "granite-guardian", "granite-guardian": 56, "key": "reliability", "llama-guard": 38, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 8, "edge": "granite-guardian", "granite-guardian": 60, "key": "schema", "llama-guard": 52, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 2, "edge": "granite-guardian", "granite-guardian": 69, "key": "ergonomics", "llama-guard": 67, "name": "Agent ergonomics", "weight": 13 }, { "by": 5, "edge": "granite-guardian", "granite-guardian": 58, "key": "security", "llama-guard": 53, "name": "Security \u0026 auth", "weight": 14 }, { "by": 15, "edge": "granite-guardian", "granite-guardian": 60, "key": "payments", "llama-guard": 45, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 19, "edge": "granite-guardian", "granite-guardian": 47, "key": "maintenance", "llama-guard": 28, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 15, "edge": "granite-guardian", "granite-guardian": 70, "key": "transparency", "llama-guard": 55, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Granite Guardian scores 60.1 (C) on agent readiness against Llama Guard 4's 49.1 (D), and leads in every scored category. Both do guard moderation.", "verdicts": { "granite-guardian": "One ungated Apache 2.0 model judges harm, jailbreaks, RAG groundedness, function-call errors and custom criteria, with signed weights and published evaluation code. It is trained and tested on English only, each call checks one criterion, the 4.1 prompt format differs from 3.x, and IBM's watsonx.ai lists only the deprecated 3.0 model.", "llama-guard": "A single self-hosted model classifies text and multi-image prompts against 14 MLCommons-aligned hazard categories and answers in a few tokens. The weights have not changed since 29 April 2025, download access needs Meta's manual approval, and the licence withholds the grant from individuals and companies based in the European Union." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard", "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard.md", "slim": "https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard.min.md" }, "markdown": "Granite Guardian scores 60.1 (C) on agent readiness against Llama Guard 4's 49.1 (D), and leads in every scored category. Both do guard moderation.\n\n- Granite Guardian: grade C, 60.1/100, rank #478 of 842. Markdown https://www.anchorterminal.com/tools/granite-guardian.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-guardian.json\n- Llama Guard 4: grade D, 49.1/100, rank #713 of 842. Markdown https://www.anchorterminal.com/tools/llama-guard.md · JSON https://www.anchorterminal.com/api/v1/tools/llama-guard.json\n\n## Which one, for what\n\n### Granite Guardian (C)\n\nGood for: A team with a GPU that wants one English-language judge for harm, jailbreaks, RAG groundedness, function-call checks and house rules, under a permissive licence with no gate.\n\nAhead on:\n- Reliability, 56 against 38\n- Schema \u0026 documentation, 60 against 52\n- Security \u0026 auth, 58 against 53\n- Payments \u0026 pricing, 60 against 45\n- Maintenance \u0026 community, 47 against 28\n- Transparency \u0026 trust, 70 against 55\n\nWatch for: Trained and tested on English only, per the model card\n\n### Llama Guard 4 (D)\n\nGood for: A team outside the EU with a GPU that wants content moderation of text and images on its own hardware, against a fixed 14-category policy it can edit in the prompt.\n\nWatch for: Weights last changed on 29 April 2025, with no changelog, version tags or stated deprecation policy\n\n\n## Score by category\n\n| Category | Weight | Granite Guardian | Llama Guard 4 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 56 | 38 | Granite Guardian +18 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 60 | 52 | Granite Guardian +8 |\n| Agent ergonomics | 13% (16.2 this run) | 69 | 67 | Granite Guardian +2 |\n| Security \u0026 auth | 14% (17.5 this run) | 58 | 53 | Granite Guardian +5 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 45 | Granite Guardian +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 47 | 28 | Granite Guardian +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 70 | 55 | Granite Guardian +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **60.1 · C** | **49.1 · D** | |\n\n## Facts side by side\n\n| Fact | Granite Guardian | Llama Guard 4 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | IBM | Meta |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache 2.0 for the weights and the repository | Llama 4 Community Licence (source-available weights, not an OSI licence), with the Llama 4 acceptable use policy |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-04-29 | 2025-04-29 |\n| Terms last updated | no document linked | 2025-04-05 |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | not found in the text |\n| Terms restrict automated access | | not found in the text |\n| Terms restrict benchmarking | | not found in the text |\n| Terms or service can change without notice | | not found in the text |\n| Arbitration or class-action waiver | | not found in the text |\n| Popularity | 182 stars | 4.4k stars |\n\n## Verdicts\n\n**Granite Guardian.** One ungated Apache 2.0 model judges harm, jailbreaks, RAG groundedness, function-call errors and custom criteria, with signed weights and published evaluation code. It is trained and tested on English only, each call checks one criterion, the 4.1 prompt format differs from 3.x, and IBM's watsonx.ai lists only the deprecated 3.0 model.\n\n**Llama Guard 4.** A single self-hosted model classifies text and multi-image prompts against 14 MLCommons-aligned hazard categories and answers in a few tokens. The weights have not changed since 29 April 2025, download access needs Meta's manual approval, and the licence withholds the grant from individuals and companies based in the European Union.\n\n## Before you call either\n\n### Granite Guardian\n\n1. Append the `\u003cguardian\u003e` block as the final user message, with the mode line, `### Criteria:` and `### Scoring Schema:`. Copy the strings from the model card, because no package builds them\n2. Use the no-think instruction for gating and parse `\u003cscore\u003e`. Think mode writes a reasoning trace first, and the card's examples allow up to 2,048 output tokens\n3. Treat `yes` as the criterion being met, which for built-in criteria means the risk is present. Treat a missing `\u003cscore\u003e` tag as a failed check\n4. Pass retrieved text through `documents=` and tool schemas through `available_tools=` in `apply_chat_template`, not inside the message text\n5. Under Ollama, set `num_ctx` in the request options. IBM's docs say the default context is short and long requests are truncated\n\n### Llama Guard 4\n\n1. Request access on the Hugging Face page before anything else. Approval is manual, and the form cannot be edited after submission\n2. Send only the user turn to check an input, and the user turn plus the model's answer to check an output. The template picks the role from the message count\n3. Parse the first line for `safe` or `unsafe` and the second for category codes. Set `max_new_tokens` to about 10 and turn sampling off\n4. Do not send an image with no text. Meta says the model is not an image-only classifier, and S14 is skipped when an image is present\n5. Pair it with a prompt-attack detector. The card says the model can itself be moved by adversarial or injected text\n\n## Questions\n\n### Which is better for AI agents, Granite Guardian or Llama Guard 4?\n\nGranite Guardian scores 60.1 (C) on agent readiness against Llama Guard 4's 49.1 (D), and leads in every scored category.\n\n### Do Granite Guardian and Llama Guard 4 need an API key?\n\nNeither needs a key.\n\n### Can an agent call Granite Guardian and Llama Guard 4 without installing anything?\n\nNo hosted endpoint is listed for Granite Guardian. No hosted endpoint is listed for Llama Guard 4.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard.json, and with the fewest tokens: https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"granite-guardian\", \"b\": \"llama-guard\"}`. From a terminal: `anchor compare granite-guardian llama-guard`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/granite-guardian.json and https://www.anchorterminal.com/api/v1/tools/llama-guard.json\n\n## Other comparisons with Granite Guardian or Llama Guard 4\n\n- [Amazon Bedrock Guardrails vs Granite Guardian](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-granite-guardian.md)\n- [Azure AI Content Safety (Prompt Shields) vs Granite Guardian](https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-granite-guardian.md)\n- [Cisco AI Defense Inspection API vs Granite Guardian](https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-granite-guardian.md)\n- [Google Cloud Model Armor vs Granite Guardian](https://www.anchorterminal.com/compare/google-model-armor-vs-granite-guardian.md)\n- [Granite Guardian vs LlamaFirewall](https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall.md)\n- [Amazon Bedrock Guardrails vs Llama Guard 4](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llama-guard.md)\n- [Azure AI Content Safety (Prompt Shields) vs Llama Guard 4](https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llama-guard.md)\n- [Cisco AI Defense Inspection API vs Llama Guard 4](https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llama-guard.md)\n- [Google Cloud Model Armor vs Llama Guard 4](https://www.anchorterminal.com/compare/google-model-armor-vs-llama-guard.md)\n- [Granite Guardian vs Guardrails AI](https://www.anchorterminal.com/compare/granite-guardian-vs-guardrails-ai.md)\n- [Granite Guardian vs Lakera Guard (Check Point AI Guardrails)](https://www.anchorterminal.com/compare/granite-guardian-vs-lakera-guard.md)\n- [Granite Guardian vs Mistral Moderation API](https://www.anchorterminal.com/compare/granite-guardian-vs-mistral-moderation.md)\n- [Granite Guardian vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/granite-guardian-vs-nemo-guardrails.md)\n- [Granite Guardian vs OpenAI Guardrails](https://www.anchorterminal.com/compare/granite-guardian-vs-openai-guardrails.md)\n- [Granite Guardian vs OpenAI Moderation API](https://www.anchorterminal.com/compare/granite-guardian-vs-openai-moderation.md)\n- [Granite Guardian vs Prisma AIRS AI Runtime Security API](https://www.anchorterminal.com/compare/granite-guardian-vs-prisma-airs.md)\n- [Guardrails AI vs Llama Guard 4](https://www.anchorterminal.com/compare/guardrails-ai-vs-llama-guard.md)\n- [Lakera Guard (Check Point AI Guardrails) vs Llama Guard 4](https://www.anchorterminal.com/compare/lakera-guard-vs-llama-guard.md)\n- [Llama Guard 4 vs Mistral Moderation API](https://www.anchorterminal.com/compare/llama-guard-vs-mistral-moderation.md)\n- [Llama Guard 4 vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/llama-guard-vs-nemo-guardrails.md)\n- [Llama Guard 4 vs OpenAI Guardrails](https://www.anchorterminal.com/compare/llama-guard-vs-openai-guardrails.md)\n- [Llama Guard 4 vs OpenAI Moderation API](https://www.anchorterminal.com/compare/llama-guard-vs-openai-moderation.md)\n- [Llama Guard 4 vs Prisma AIRS AI Runtime Security API](https://www.anchorterminal.com/compare/llama-guard-vs-prisma-airs.md)\n- [Granite Guardian vs Presidio](https://www.anchorterminal.com/compare/granite-guardian-vs-microsoft-presidio.md)\n- [Llama Guard 4 vs Presidio](https://www.anchorterminal.com/compare/llama-guard-vs-microsoft-presidio.md)\n- [Llama Guard 4 vs LlamaFirewall](https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Granite Guardian vs Llama Guard 4", "url": "" } ], "description": "Granite Guardian scores 60.1 (C) on agent readiness against Llama Guard 4's 49.1 (D), and leads in every scored category. Both do guard moderation. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Granite Guardian C 60.1", "Llama Guard 4 D 49.1", "scores" ], "h1": "Granite Guardian vs Llama Guard 4", "image": "https://www.anchorterminal.com/assets/og/compare-granite-guardian-vs-llama-guard.png", "path": "/compare/granite-guardian-vs-llama-guard", "published": "2026-10-01", "section": "tools", "title": "Granite Guardian vs Llama Guard 4 for AI agents, C 60.1 vs D 49.1", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-llama-guard" }, "tokens": { "markdown": 2650, "slim": 630 }, "version": 1 }