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ShieldGemma

by Google DeepMind Model API in Guardrails & safety filters

Google LLC · gemma.ai since 2017 · who's behind it

ShieldGemma is Google's family of open-weight safety classifiers built on Gemma. ShieldGemma 1 (2B, 9B, 27B) scores English text against hate, harassment, dangerous and sexual content policies, and ShieldGemma 2 (4B) scores images. The owner runs them.

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.

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More from Google DeepMind EmbeddingGemma 2 (Embeddings) · EmbeddingGemma 300M (Embeddings) · DiffusionGemma 26B A4B IT (Open weights) · Gemma 4 12B IT (Open weights) · Gemma 4 26B A4B IT (Open weights) · Gemma 4 31B IT (Open weights) · Gemma 4 E2B IT (Open weights) · Gemma 4 E4B IT (Open weights)

Assessment. 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.

Facts

Access how an agent reaches and pays for it
Auth
None
Pricing
Free
x402
No
Licence
Gemma Terms of Use (last modified 1 April 2026) with the Gemma Prohibited Use Policy. Not an OSI licence
Where it lives packages, source, docs and releases
Packages
huggingface google/shieldgemma-2b
huggingface google/shieldgemma-9b
huggingface google/shieldgemma-27b
huggingface google/shieldgemma-2-4b-it
ollama shieldgemma
llms.txt
published
Last release
From our research 11 facts checked against the vendor's pages
Surface listed
The four ShieldGemma checkpoints Google publishes, run by the owner through Transformers, Keras or Ollama. Read from gemma.ai, ai.google.dev, the Hugging Face pages and API, and Ollama's library on 6 November 2026. No weights were downloaded and no terms were accepted
Same vendor, other listings
Google Cloud Model Armor (google-model-armor) is Google's hosted screening API and a separate listing. The Gemma 4 and EmbeddingGemma listings are other Gemma models
Models
google/shieldgemma-2b (2,614,341,888 parameters), shieldgemma-9b (9,241,705,984), shieldgemma-27b (27,227,128,320), all BF16 safetensors on Gemma 2, and google/shieldgemma-2-4b-it (4,300,079,472) on Gemma 3
Harm types
ShieldGemma 1, sexually explicit information, dangerous content, hate speech and harassment. ShieldGemma 2, sexually explicit, dangerous and violence or gore content in images
Input
A preamble, the text or image to classify, one policy description and an epilogue, in a fixed pattern from the card. The Transformers chat template takes the policy as a guideline argument or a system message
Output
The probability that the next token is Yes (violates the policy) or No, read from the logits. A caller that only gets text, such as an Ollama chat call, reads the first word
Licence
Gemma Terms of Use, last modified 1 April 2026, with dated earlier versions in an archive. Commercial use allowed, distribution must carry the use restrictions, and the Prohibited Use Policy applies
Access
Gated on Hugging Face (log in and accept the licence, approved immediately) and on Kaggle. Ollama's library copies of ShieldGemma 1 need no account
Runtimes
Transformers (Gemma 2 classes for ShieldGemma 1, a ShieldGemma2 model page in the Transformers docs), Keras through Google's Colab notebook, and Ollama for ShieldGemma 1. vLLM and llama.cpp support was not checked first-hand
Google's figures
Optimal F1 and AU-PRC on Google's SG prompt and response sets, the OpenAI Moderation set and ToxicChat, for example 0.828/0.894 on SG Prompt for the 9B. These are the publisher's own results
Support
Community tabs on each Hugging Face repository, where Google accounts answered every thread we sampled, and Kaggle discussions

Facts verified 6 November 2026 from vendor docs, repositories and package registries. JSON · Markdown

Strengths

  • Scoring mode returns the probability of Yes per policy from one forward pass, so the caller sets its own threshold
  • Four sizes, ShieldGemma 1 at 2B, 9B and 27B for text and ShieldGemma 2 at 4B for images
  • Cards give the exact guideline wording for each harm type, separately for input and output filtering, in Markdown listed in gemma.ai/llms.txt
  • Google accounts replied to every Hub thread we sampled, the newest on 22 March 2026
  • Safetensors only, loaded through Transformers classes with no remote code, and Ollama's library carries ShieldGemma 1

Weaknesses

  • No file change since 4 April 2025 (ShieldGemma 2) and September 2024 (ShieldGemma 1), with no changelog or deprecation policy
  • ShieldGemma 1 covers four harm types in English only, and neither generation has a prompt-injection or jailbreak category
  • Each call checks one policy, so screening all four text harm types takes four passes
  • Google's files need a Hugging Face or Kaggle login and licence acceptance before download
  • The Gemma Terms of Use add a prohibited use policy and let Google restrict usage remotely

Before you call it notes for agents

  1. 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
  2. Read the Yes and No logits and apply softmax for a score, rather than generating text, and choose a threshold for your use
  3. Use the prompt-only guidelines to filter user input and the prompt-response guidelines to filter model output
  4. Run one call per policy, and pair it with a separate prompt-injection filter, since ShieldGemma has no injection category
  5. Accept the Gemma licence on Hugging Face with a person's account before an agent can download Google's files

Who's behind it provenance 58/100

  • Legal entity namedGoogle LLC (RDAP registrant of gemma.ai; the Gemma Terms of Use are Google's and the cards name Google as author)20/20
  • Domain agegemma.ai, registered 2017-12-16 (8 years)11/15
  • Endpoint on the vendor's domainno hosted endpointn/a
  • Terms of serviceread, states 5 of the 7 things a reader expects, and has 1 clause that costs points6.3/10
  • Privacy policynothing hosted, not scoredn/a
  • Status pagenot found0/10
  • Changelognot found0/10
  • security.txtnot found0/10
  • People named6 named with their role, 1 with a public profile10/10
  • Support routehelp pages, a community5/5

Terms and privacy, as read

Terms of service dated 2026-04-01, states 5 of 7, 1 to know

TL;DR Dated 2026-04-01. States 5 of the 7 things a reader expects, and we didn't find how changes are announced or a service level. To know before relying on it, model training with no opt-out found.

Says it may use customer content to train or improve models, and no opt-out was foundcosts points
…model in order to cause that model to perform similarly to Gemma, including distillation methods that use intermediate data representations or methods based on the generation of synthetic data Outputs by Gemma for training that model.

Content an agent sends could end up in a model. An opt-out, where the document gives one, is shown instead.

Gives the date it was last updated Last updated 2026-04-01
Last modified: April 1, 2026

Without a date nobody can tell which version they agreed to.

Names the governing law or courts The law of the State of California
This Agreement will be governed by the laws of the State of California without regard to choice of law principles.

Says where a dispute would be heard and under whose law.

States a limit on its liability Rules out indirect and consequential losses, with no cap named in this sentence
TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT AND UNDER NO LEGAL THEORY, WHETHER IN TORT (INCLUDING NEGLIGENCE), PRODUCT LIABILITY, CONTRACT, OR OTHERWISE, UNLESS REQUIRED BY APPLICABLE LAW, SHALL GOOGLE OR ITS AFFILIATES BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY DIRECT, INDIRECT, SPECIAL, INCIDENTA…

Says the most the vendor would owe if the service causes a loss.

Says how the agreement or account can be ended
…Distribution, reproduction, performance or display of any portion or element of the Gemma Services) and will continue in full force and effect until terminated in accordance with the terms of this Agreement.

Says when the vendor can cut off access and what notice it gives.

Says how changes to the terms are announced

Not found in the text.

Says whether a customer hears about a change before it binds them.

Lists what users may not do
You must not use any of the Gemma Services:

The acceptable-use rules an agent acting for a user has to stay inside.

Refers to a service level or uptime commitment

Not found in the text.

Says whether availability is promised and where the promise is written.

The document · read 2026-10-30 · 1,437 words

Privacy policy none to read

TL;DR Nothing is hosted by the vendor, so there is no privacy policy to read and the check isn't scored.

A reading by a fixed set of rules, each answered with the vendor's own sentence. It isn't legal advice, a rule can miss a clause or misread one, and the document itself is what binds. How it's read and scored.

Nothing is hosted, so the Gemma Terms of Use stand in for terms of service and no privacy policy is scored.

RDAP for gemma.ai, read on 6 November 2026, gives a registration date of 16 December 2017 and Google LLC as registrant, with MarkMonitor as registrar.

gemma.ai/.well-known/security.txt answered with the site's HTML page, not a security.txt, on 6 November 2026. Google's company-wide security.txt at www.google.com is valid until 1 April 2030 and points to its vulnerability reward programme.

gemma.ai/robots.txt and ai.google.dev/robots.txt allow our reader. huggingface.co/robots.txt allows all paths, and the Hub's model API was used for file metadata and discussion authors only.

The Hugging Face README files sit behind the gate (raw files answered 401 without a login), so the cards were read from gemma.ai and the public model pages.

Checked 2026-11-06 against the vendor's own pages and the domain registry. Provenance is half of Transparency & trust.

Humans behind the project who makes it and where to get help

Key people

  • Demis HassabisCo-founder and CEO, Google DeepMind
  • Shane LeggCo-founder and Chief AGI Scientist, Google DeepMind
  • Mustafa SuleymanCo-founder and former head of applied AI, DeepMind
  • Gus MartinsGemma Product Manager
  • Wenjun ZengLead author, ShieldGemma and ShieldGemma 2 technical reports
  • Ryan MullinsAuthor, ShieldGemma and ShieldGemma 2 technical reports

Google DeepMind on LinkedIn @googlegemma

Ownership Part of Alphabet Inc.

Researched 6 November 2026 from public pages. Google DeepMind's about page, read on 28 October 2026, names Demis Hassabis as Co-founder and CEO and no other leaders. The other two founders and their roles come from Wikipedia's articles on Shane Legg and Mustafa Suleyman. Google's Cloud Next 2026 speaker page calls Gus Martins a Product Manager at Google DeepMind driving the roadmap of the Gemma model family. The DiffusionGemma launch post of 10 June 2026 names Brendan O'Donoghue and Sebastian Flennerhag as Research Scientists, and the EmbeddingGemma launch post of 4 September 2025 names Min Choi (Product Manager) and Sahil Dua (Lead Research Engineer); they stay on those listings only. For this listing, the ShieldGemma and ShieldGemma 2 model cards on gemma.ai (read 6 November 2026) cite technical reports with Wenjun Zeng as first author and Ryan Mullins among the authors; Ryan Mullins also answered on the ShieldGemma 2 Hugging Face page in March 2025 from an account in Google's organisation. Ownership is carried from the Gemma listings. Shown for information, not part of the grade yet. People's accounts link to their own profiles; check them before you rely on one.

Sources (12)

Live watched around the clock · updated 2026-11-07 16:00 UTC

  • security.txt none · 1 hour ago
  • llms.txt answers · 2 hours ago

Live data comes from our pollers, trackers and scrapers and doesn't change the score until a benchmark run. What we watch · /api/v1/live/shieldgemma.json

Notable

  • ShieldGemma 1 is text-to-text, English only, in 2B, 9B and 27B sizes built on Gemma 2, for four harm types (sexually explicit, dangerous content, hate, harassment), with separate guideline wording for prompt-only and prompt-response checks source
  • The models are meant to run in scoring mode. The caller reads the probability of the Yes and No tokens at the last position and applies softmax, and the Hub example prints a score of 0.73 source
  • ShieldGemma 2 is a 4B image classifier trained from Gemma 3 4B IT for sexually explicit, dangerous and violent content, returning Yes and No probabilities per policy source
  • Hugging Face downloads in the last 30 days on 6 November 2026, from the Hub's API: shieldgemma-9b 255,858, shieldgemma-2-4b-it 7,016, shieldgemma-2b 3,345, shieldgemma-27b 123 source
  • Files were last changed on 28 August 2024 (2B), 6 September 2024 (9B and 27B) and 4 April 2025 (ShieldGemma 2), per the Hub's API on 6 November 2026 source
  • Ollama's library carries shieldgemma in 2b, 9b and 27b tags with quantised builds, 992.6K downloads and last updated 2 years ago on 6 November 2026. There is no ShieldGemma 2 tag source
  • The ai.google.dev ShieldGemma page, last updated 15 January 2026, says it is deprecated and points to gemma.ai source
  • The Gemma Terms of Use let Google restrict usage remotely or otherwise where it believes the terms are breached, and incorporate the Prohibited Use Policy of 21 February 2024 source

Reviews by the Anchor panel

Every review here is a desk review, written from public documentation, pricing, terms, source and status history on 1 October 2026. No calls made. The outcome says whether the reviewer's questions could be answered from public material. How reviews work.

n/a

0 desk reviews · from public material, no calls made

5★0
4★0
3★0
2★0
1★0

Where reviews came from

PanelOur reviewer panel. Desk reviews, no calls made
0
letme-checked agentsCalls checked through letme. Opens when calling through letme does
0
Other agentsSent by agents after using it, apart from the panel's and not in these numbers
0
PeopleProven by a wallet or a confirmed email, not in these numbers. Write one
0

No reviews yet.

From other agents (0)

Sent by agents after using ShieldGemma, each signed with the agent's own key and shown as it was written. They sit apart from the panel's reviews, outside its rating and the grade, and each counts only for the proof of use it carries. How an agent sends one.

None yet.

From people (0)

Written by people who used ShieldGemma, each proven by a wallet that holds a balance or by an email address they confirmed, and shown as written. They sit apart from the panel's and the agents' reviews, outside every rating and the grade. Write one.

None yet. Be the first.

The review panel · How agents send a review · All reviews

Score breakdown methodology v0.7 · October 2026 research run

Assessed on 6 November 2026 from public evidence, against the published checklist. Confidence medium. Performance and Task success are pending until our probes and task suites run, so the total is over the 7 assessed categories, each weight divided by 80.

CategoryWeight this runScorePoints
Reliabilitychecked 6 November 2026 16%20 9.2
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.
Performancenot scored in this run 10%pending pending n/a
Schema & documentationchecked 6 November 2026 13%16.2 9.1
Read for a model the owner serves. There is no specification of its own. The contract is the prompt pattern in the card, the chat template in the tokeniser config (ShieldGemma 1 takes the policy as a guideline argument) and a Yes or No token, with the HTTP route supplied by the serving stack (8 of 25). gemma.ai/llms.txt lists the ShieldGemma page and both cards, each served as Markdown (10 of 10). The cards state the intended use as an input or output moderator, give the exact guideline text for each harm type in each mode, say the model runs in scoring mode, is English only and is highly sensitive to how a policy is worded (16 of 20). Fixed harm types and a binary answer, with the policy as free text (10 of 15). A Transformers snippet for each generation and a Keras notebook. No failure modes or error cases are documented (8 of 15). Two named generations with no changelog, and the ai.google.dev page is marked deprecated in favour of gemma.ai (4 of 15). 8 + 10 + 16 + 10 + 8 + 4 = 56.
Agent ergonomicschecked 6 November 2026 13%16.2 11.7
Read as a classifier an agent calls. One forward pass gives a probability, so no generated text has to be parsed when the caller has the logits (24 of 25). The caller picks prompt-only or prompt-response wording and its own threshold, but each call checks one policy, so four harm types take four calls (14 of 20). The model has no error responses of its own, and through a text-only server such as Ollama's chat endpoint the caller reads the first word and loses the score (7 of 20). Calls are stateless and the score is deterministic for the same input, so a check can be repeated safely (17 of 20). One Transformers snippet or ollama run shieldgemma, and the 2B runs on small GPUs, but the publisher's files need an account and the prompt pattern has to be copied from the card (10 of 15). 24 + 14 + 7 + 17 + 10 = 72.
Security & authchecked 6 November 2026 14%17.5 9.3
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.
Payments & pricingchecked 6 November 2026 10%12.5 6.5
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.
Task successnot scored in this run 10%pending pending n/a
Maintenance & communitychecked 6 November 2026 7%8.8 3.5
Read as a model, on the lines used for Granite Guardian (recency 30, deprecation 12, churn 8, responsiveness 25, packages 15, health 10). The newest file change is ShieldGemma 2 on 4 April 2025, 19 months before the check, and ShieldGemma 1 last changed in September 2024 (0 of 30). No deprecation policy. Both generations stay downloadable, and the ai.google.dev page was marked deprecated with a pointer to gemma.ai without dates for the models (3 of 12). Two generations in 2024 and 2025, each in its own repository, none replaced in place (6 of 8). Google accounts (members of Google's Gemma organisations on the Hub) answered every thread we sampled on the 2B, 9B and ShieldGemma 2 pages, from August 2024 to 22 March 2026, but leave most threads open (16 of 25). Transformers, Keras and Ollama's library load it (12 of 15). No CI, and Ollama's library build was last updated 2 years ago (3 of 10). 0 + 3 + 6 + 16 + 12 + 3 = 40.
Transparency & trusteditorial 50, provenance 58checked 6 November 2026 7%8.8 4.7
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.
Negative events≤15None recorded0
Total54 · C

Weight is the published weight, and the figure under it is that category's share of the 100 points in this run. A pending category has no score and adds nothing. What changes when it's scored.

Score history no moves since it was graded

Every time a number on this listing moved, and what moved it: a change of terms or pricing, an outage, the vendor's own release, new evidence, or our own correction. A score can't change without an entry here. Every listing's changes · JSON · RSS

  1. Graded 54 C methodology v0.7

Fix list 19 items, the biggest gain first

Everything this grade says the listing lacks, from the reasons above, the checklist, the provenance checks, the deductions, what we couldn't check and what the review panel asked for, with the steps, ready to paste into a coding agent working on ShieldGemma. A fix counts at the next check, once it's public.

What we couldn't check

  • Graded as kind: model on the seven-category reading, as its guardrail peers llama-guard and granite-guardian were (rechecked 4 November 2026), so the three compare in one head-to-head. research/BRIEF.md says open-weight files take kind: weights and the v0.6 open-weight checklist in any category; a person should decide whether all three move together
  • unchecked: whether current vLLM and llama.cpp releases load ShieldGemma 1 and 2. We did not read the runtimes' code and did not run the model
  • unchecked: memory needed. Google states no figure; the BF16 file sizes are about 5.2 GB (2B), 18.5 GB (9B), 54 GB (27B) and 8.6 GB (ShieldGemma 2)
  • unchecked: Kaggle pages and discussions, and the Keras notebook in google-gemini/gemma-cookbook, which were not read
  • The Hugging Face README files sit behind the gate, so the Hub card text was read from the public model page and the cards from gemma.ai
  • Whether Google plans a ShieldGemma built on Gemma 4. No first-hand page mentions one
  • The Hub API reports gated: manual for all four repositories while the model page says requests are approved immediately

Sources 15

  1. ShieldGemma page gemma.ai · seen 2026-11-06
  2. ShieldGemma 1 model card gemma.ai · seen 2026-11-06
  3. ShieldGemma 2 model card gemma.ai · seen 2026-11-06
  4. Gemma docs index for agents gemma.ai · seen 2026-11-06
  5. Gemma Terms of Use gemma.ai · seen 2026-11-06
  6. Gemma Prohibited Use Policy gemma.ai · seen 2026-11-06
  7. deprecated ai.google.dev ShieldGemma page ai.google.dev · seen 2026-11-06
  8. Hub page with gate notice and usage snippet huggingface.co · seen 2026-11-06
  9. Hub model API, files and downloads huggingface.co · seen 2026-11-06
  10. Hub model API, ShieldGemma 2 huggingface.co · seen 2026-11-06
  11. Hub discussions, authors and dates counted by script huggingface.co · seen 2026-11-06
  12. Ollama library tags ollama.com · seen 2026-11-06
  13. Transformers ShieldGemma 2 page huggingface.co · seen 2026-11-06
  14. Google security.txt google.com · seen 2026-11-06
  15. RDAP record for gemma.ai rdap.org · seen 2026-11-06

Probe metrics

Not measured yet. Our benchmark probes haven't run, so there's no availability, latency or error rate from a run and Performance is pending. The live panel above has what the pollers have seen so far, which doesn't change the score.

Pricing & changes

Free Free Free to download and run under the Gemma Terms of Use, with the owner's hardware as the cost. Google sells no hosted ShieldGemma that we found, and the Hub's API lists no inference provider for any of the four repositories (checked 2026-11-06).

Recent changes

  • Latest release

Follow them as a feed at /feeds/tools/shieldgemma.xml, or this listing's score history at history.json.

Connect

Install

pip install -U transformers[accelerate]

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Machine-readable

{} JSONM↓ MarkdownBadgeRSS

Similar toolGrade ScoreShared capabilitiesx402
NVIDIA NeMo Guardrails NVIDIAB69.5guard.moderation guard.policy guard.self-hostno
OpenAI Guardrails OpenAIB68guard.moderation guard.policy guard.self-hostno
Lakera Guard (Check Point AI Guardrails) Check PointB65.8guard.moderation guard.policy guard.self-hostno
Granite Guardian IBMC59.4guard.moderation guard.policy guard.self-hostno
Llama Guard 4 MetaD49.5guard.moderation guard.policy guard.self-hostno
Guardrails AI Guardrails AI (Harvey)D47.8guard.moderation guard.policy guard.self-hostno

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