Head to head · Content moderation · October 2026 research run
Granite Guardian vs ShieldGemma
Granite Guardian scores 59.4 (C) on agent readiness against ShieldGemma's 54 (C), and leads in 5 of 7 scored categories. Both do content moderation.
Best guardrails and safety filters for AI agents · All 155 guardrails comparisons
Which one, for what
Best 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.
Ahead on
- Reliability, 56 against 46
- Security & auth, 58 against 53
- Payments & pricing, 60 against 52
- Transparency & trust, 71 against 54
Watch for
Trained and tested on English only, per the model card
Best for Policy-specific content moderation of English text input or output, or of images, on the owner's hardware, with a probability to threshold.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
No file change since 4 April 2025 (ShieldGemma 2) and September 2024 (ShieldGemma 1), with no changelog or deprecation policy
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Transparency & trust Granite Guardian +17
Granite Guardian 71
Weights and repository are under the Apache 2.0 licence with no gate and no use policy attached (30 of 30). Inputs stay on the owner's hardware, so no privacy statement applies. Training data is described as hh-rlhf samples annotated at DataForce plus synthetic data, and the datasets are not released (issue 27, open since 28 March 2025) (22 of 30). No deprecation policy for the open weights. Older versions stay downloadable, and watsonx.ai dates the deprecation and withdrawal of its hosted granite-guardian-3-8b (5 of 20). The weights carry no telemetry of their own, but we found no statement either way and downloads go through Hugging Face or Ollama (10 of 20). 30 + 22 + 5 + 10 = 67.
ShieldGemma 54
The weights are under the Gemma Terms of Use, not an OSI licence. They carry distribution conditions, the Prohibited Use Policy and a clause that lets Google restrict usage remotely where it believes the terms are breached. The terms are dated (1 April 2026) with earlier versions archived (15 of 30). Inputs stay on the owner's hardware, so no privacy statement applies. ShieldGemma 1 was fine-tuned on synthetic internal data and public datasets described in a technical report, and ShieldGemma 2 on a WebLI subset and synthetic images with CSAM filtering. No data is released (20 of 30). No deprecation policy or dated model retirements (5 of 20). The weights carry no telemetry of their own, with no statement either way, and downloads go through Hugging Face, Kaggle or Ollama (10 of 20). 15 + 20 + 5 + 10 = 50.
Reliability Granite Guardian +10
Granite Guardian 56
Scored on the local-software lines, since the owner runs the model. Weights are ungated on Hugging Face, IBM publishes GGUF builds and Ollama carries granite4.1-guardian:8b. The card's install line is pip install transformers torch vllm with no versions, and the evaluation code asks for vllm>=0.15.1 and transformers>=4.52 and names an 80 GB GPU. No Python version is stated (14 of 20). The repository has no CI workflow and no tests. Its evaluation folder reproduces the card's benchmark figures, which is public but is not run automatically (5 of 25). Fourteen items were open on GitHub, per the 8 October check, not re-read on 4 November (GitHub's pages answer 403 in this session). Five are automated dependency alerts, one is an outside pull request, and three usage problems from May to September 2025 (issues 28, 29 and 35, on a 3.2 error and on Ollama) are open with three to seven comments each. The 4.1 Hugging Face page has no open thread (14 of 25). Versions are named 3.0 to 4.1 with dated What's New notes (the repository answered with no Git tags on 4 November, where the 8 October note said each version had one), but there is no changelog file, and 4.1 changed the prompt format from the guardian_config argument of the 3.x cookbooks to a <guardian> block without a migration note (9 of 15). Released as 4.1 with no preview label. IBM calls model signing experimental (14 of 15). Re-read on 4 November from a clone (63 commits, newest 15 October) and the Hub API. The 4.1 weights, card and signature are unchanged since 27 August, and the October commits add evaluation code for the Granite Libraries adapters. 14 + 5 + 14 + 9 + 14 = 56.
ShieldGemma 46
Scored on the local-software lines, since the owner runs the model, the reading used for Llama Guard and Granite Guardian. Google's install line is pip install -U transformers[accelerate] with no versions, a Keras Colab notebook covers ShieldGemma 1, and Ollama's own library carries ShieldGemma 1. No Python version or memory figure is stated, and the publisher's files sit behind a login and licence click-through (12 of 20). No CI, tests or evaluation code for the models were found. The technical reports describe the evaluation and nothing reruns it (0 of 25). On the Hub, 8 of 23 threads on the 2B, 2 of 10 on the 9B, none of 8 on the 27B and 9 of 10 on ShieldGemma 2 are open, but every open thread we sampled has a reply from a Google account, the newest on 22 March 2026 (15 of 25). No changelog or version tags. The two generations are named and sit in their own repositories (4 of 15). Released with no preview label (15 of 15). 12 + 0 + 15 + 4 + 15 = 46.
Payments & pricing Granite Guardian +8
Granite Guardian 60
Self-hosted rule. Nothing to buy for the model, and the Apache 2.0 licence allows commercial use at no charge (20). Free to run with no card (20). The weights are not gated, so an agent can fetch and run them with no sign-up (20). No payment protocol (0). IBM's watsonx.ai sells only the deprecated ibm/granite-guardian-3-8b at $0.0002 per 1,000 tokens, which is not the model graded here.
ShieldGemma 52
Self-hosted rule. Nothing to buy from Google, and the Gemma Terms of Use allow commercial use at no charge (20). Free to run with no card (20). Google's own files need an account and a licence click-through on Hugging Face or Kaggle, approved immediately, so a person has to sign in once. Ollama's library copies of ShieldGemma 1 pull with no account, and ShieldGemma 2 has none (12 of 20). No payment protocol (0). No hosted ShieldGemma from Google or an inference provider was found. 20 + 20 + 12 + 0 = 52.
Security & auth Granite Guardian +5
Granite Guardian 58
Read as a model the owner runs, on the model lines, with retention and training in place of the read-only line. No account, key or token is needed to get or run the weights, so there is no secret to leak, and any server authentication is the owner's to add (14 of 30). Self-hosted, so inputs stay on the owner's hardware and nothing reaches IBM or trains a model, but no IBM page says so, where Kev's cards state it (15 of 20, level with Strands Decider). It reads untrusted text by design and has a built-in jailbreaking criterion. The card says the model may be prone to adversarial attacks and that reasoning traces may contain unsafe content, with no mitigation guidance beyond keeping to the scoring mode (8 of 15). No call log of its own. Think mode gives a reason for each judgement (6 of 15). IBM's security.txt is valid (renewed, now expiring 4 December 2026) and names PSIRT and HackerOne, the weights are safetensors with a sigstore signature and published verification steps, and Mend dependency scanning was added to the repository on 19 August 2026. The repository still has no SECURITY.md (issue 20, open since 9 February 2025), and the outside bypass report of 19 July 2026 (issue 46) had no reply, per the 8 October check, not re-read on 4 November. No IBM security bulletin for Granite Guardian was found (15 of 20). 14 + 15 + 8 + 6 + 15 = 58.
ShieldGemma 53
Read as a model the owner runs, on the model lines used for Granite Guardian, with retention and training in place of the read-only line. No key is needed to run it. Google's files need a Hugging Face login and licence acceptance, approved immediately, so there is a token to download but no secret at run time (13 of 30). Self-hosted, so inputs stay on the owner's hardware and nothing reaches Google, though no Google page says so (15 of 20). It reads untrusted text by design. The card says the model is highly sensitive to the policy wording and may behave unpredictably with ambiguous language, and gives no prompt-injection guidance (6 of 15). No call log of its own, though each call returns a score (5 of 15). Weights are safetensors only and load through Transformers classes with no remote code. Google's security.txt is valid and points to its reward programme, and there is no model-specific security page or advisory record (14 of 20). 13 + 15 + 6 + 5 + 14 = 53.
Score by category
| Category | Weight this run | Granite Guardian | ShieldGemma | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 56 | 46 | Granite Guardian +10 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 60 | 56 | Granite Guardian +4 |
| Agent ergonomics | 13%16.2 | 69 | 72 | ShieldGemma +3 |
| Security & auth | 14%17.5 | 58 | 53 | Granite Guardian +5 |
| Payments & pricing | 10%12.5 | 60 | 52 | Granite Guardian +8 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 38 | 40 | ShieldGemma +2 |
| Transparency & trust | 7%8.8 | 71 | 54 | Granite Guardian +17 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 59.4/100 | C 54/100 |
Facts side by side
| Fact | Granite Guardian | ShieldGemma |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | IBM | Google DeepMind |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache 2.0 for the weights and the repository | Gemma Terms of Use (last modified 1 April 2026) with the Gemma Prohibited Use Policy. Not an OSI licence |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2026-04-29 | 2025-04-04 |
| Terms last updated | no document linked | 2026-04-01 |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | not read yet | yes |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Popularity | 182 stars | none |
| Agent reviews | 3.3/5 (4) | none |
How the scores have moved
ShieldGemma
No score change since it was listed.
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.
ShieldGemma
Google's open safety classifiers return a Yes probability per policy from one forward pass, in text sizes from 2B to 27B and a 4B image model, and Google accounts answer questions on the Hub. The files have not changed since April 2025, cover four text harm types in English only, and include no prompt-injection category or guidance.
Before you call either
Granite Guardian
- Append the
<guardian>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
<score>. Think mode writes a reasoning trace first, and the card's examples allow up to 2,048 output tokens - Treat
yesas the criterion being met, which for built-in criteria means the risk is present. Treat a missing<score>tag as a failed check - Pass retrieved text through
documents=and tool schemas throughavailable_tools=inapply_chat_template, not inside the message text - Under Ollama, set
num_ctxin the request options. IBM's docs say the default context is short and long requests are truncated
ShieldGemma
- Copy the prompt pattern and guideline text from the card word for word, since the card says the model is highly sensitive to policy wording
- Read the
YesandNologits and apply softmax for a score, rather than generating text, and choose a threshold for your use - Use the prompt-only guidelines to filter user input and the prompt-response guidelines to filter model output
- Run one call per policy, and pair it with a separate prompt-injection filter, since ShieldGemma has no injection category
- Accept the Gemma licence on Hugging Face with a person's account before an agent can download Google's files
Questions
Which is better for AI agents, Granite Guardian or ShieldGemma?
Granite Guardian scores 59.4 (C) on agent readiness against ShieldGemma's 54 (C), and leads in 5 of 7 scored categories.
Do Granite Guardian and ShieldGemma need an API key?
Neither needs a key.
Can an agent call Granite Guardian and ShieldGemma without installing anything?
No hosted endpoint is listed for Granite Guardian. No hosted endpoint is listed for ShieldGemma.
Other comparisons with Granite Guardian or ShieldGemma
- Amazon Bedrock Guardrails vs ShieldGemma
- Azure AI Content Safety (Prompt Shields) vs ShieldGemma
- Cisco AI Defense Inspection API vs ShieldGemma
- Google Cloud Model Armor vs ShieldGemma
- Granite Guardian vs Guardrails AI
- Granite Guardian vs Lakera Guard (Check Point AI Guardrails)
- Granite Guardian vs Llama Guard 4
- Granite Guardian vs Mistral Moderation API
- Granite Guardian vs NVIDIA NeMo Guardrails
- Granite Guardian vs OpenAI Guardrails
- Granite Guardian vs OpenAI Moderation API
- Granite Guardian vs Prisma AIRS AI Runtime Security API
- Guardrails AI vs ShieldGemma
- Lakera Guard (Check Point AI Guardrails) vs ShieldGemma
- Llama Guard 4 vs ShieldGemma
- Mistral Moderation API vs ShieldGemma
- NVIDIA NeMo Guardrails vs ShieldGemma
- OpenAI Guardrails vs ShieldGemma
- OpenAI Moderation API vs ShieldGemma
- Prisma AIRS AI Runtime Security API vs ShieldGemma
- Amazon Bedrock Guardrails vs Granite Guardian
- Azure AI Content Safety (Prompt Shields) vs Granite Guardian
- Cisco AI Defense Inspection API vs Granite Guardian
- Google Cloud Model Armor vs Granite Guardian
- Granite Guardian vs LlamaFirewall
- AgentGate vs Granite Guardian
- AgentGate vs ShieldGemma
- LlamaFirewall vs ShieldGemma
- Granite Guardian vs Presidio
- Presidio vs ShieldGemma
Machine-readable
- This page as Markdown
/compare/granite-guardian-vs-shieldgemma.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/granite-guardian.json·/api/v1/tools/shieldgemma.json - From a terminal
anchor compare granite-guardian shieldgemma(the CLI) - Over MCP
compare_tools {"a": "granite-guardian", "b": "shieldgemma"}at/mcp, no key