Google Imagen by Google

# Fix list: Google Imagen

From Anchor Terminal's listing at https://www.anchorterminal.com/tools/google-imagen, the October 2026 research run, assessed 1 October 2026. Grade F, 7.2 out of 100.

This is everything the published grade says the listing lacks, the biggest possible gain to the total first. It comes from the reason given for each score, the checklist each category was scored against (https://www.anchorterminal.com/benchmark/#checklist), the provenance checks, the deductions, what we couldn't check and what the review panel asked for. A fix counts at the next check, once it's public.

For a coding agent working on Google Imagen: work through the items below in the product, its docs and its public pages. Each category gives the reason for its score, with the points each checklist item earned, and the checklist itself, so the gap is the items that earned less than their points. Change the product, not the wording, and keep a note of what you changed and where it's published.

## 1. Reliability, 0 out of 100, up to 20 more on the total

Why it scored 0: Retired, so there's nothing left to measure. Vertex AI discontinued every Imagen endpoint on 30 June 2026 and the Gemini API shut Imagen 4 down on 17 August 2026. Every call to an imagen model name now fails (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-reliability):

Hosted APIs, MCP servers, models and platforms.

- 20, a public status page with component history (Statuspage, Instatus, BetterStack or the vendor's own).
- 0 to 30, the incident record for the last 90 days on that page. 30 for a clean record or trivial incidents only, 20 for minor incidents only, 10 for one major outage (an hour or more of a core API down, or errors across the board), 0 for several. 5 when there's no history we could read, and the note says so.
- 15, rate limits documented with numbers.
- 15, documented 429 or overload handling (Retry-After, backoff guidance), and idempotency keys or safe-retry guidance where writes are involved.
- 10, an SLA published for any paid tier.
- 10, the surface agents use is generally available, not beta or preview.

Local packages, SDKs, frameworks and stdio MCP servers.

- 20, installs from an official package with supported runtimes stated.
- 25, a public CI and test suite, passing on the default branch.
- 0 to 25, open crash or regression issues relative to activity (25 for few and handled, 0 for many, old and unanswered).
- 15, semver discipline and breaking changes called out in a changelog.
- 15, version 1.0 or later, or declared stable.

Protocols are read from their reference implementations, the public facilitators or servers, spec stability and test vectors.

## 2. Security & auth, 0 out of 100, up to 17.5 more on the total

Why it scored 0: No live surface to secure. The credential model and data terms now belong to the Gemini API and Vertex AI listings (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-security):

- 0 to 30, the credential model. 30 for OAuth 2.1 with scopes, or scoped and revocable keys with rotation. 20 for plain revocable API keys. 10 for one all-powerful key. 10 off when a secret can travel in a URL query string as a documented option.
- 0 to 20, read-only or least-privilege modes, and confirmation or approval for destructive actions.
- 0 to 15, prompt-injection posture where the tool returns untrusted content (documented mitigations or guidance). A tool that returns no untrusted content gets 10.
- 0 to 15, audit logs or per-call visibility for the operator.
- 0 to 20, a security programme. security.txt or a disclosure policy, a bug bounty, SOC 2 or ISO 27001, advisories handled in public.

Models are read for retention, whether API data trains models (and whether that's off by default), zero-retention options and certifications. Frameworks for telemetry defaults, approval hooks, guardrails and sandboxing.

## 3. Agent ergonomics, 0 out of 100, up to 16.3 more on the total

Why it scored 0: Nothing callable remains, so context cost, error handling and retries can't be assessed (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-ergonomics):

- 0 to 25, context cost. For MCP, the number and size of the tool definitions (25 for ten or fewer compact tools, 15 for 11 to 30, 5 for more than 30, plus up to 10 back for toolsets, dynamic loading or read-only subsets). For APIs, whether responses can be sized (field selection, limits, summaries).
- 20, pagination, filtering and output-size controls.
- 20, actionable, documented error responses, codes and messages an agent can recover from.
- 20, idempotency or safe retries, and for MCP the `readOnlyHint` and `destructiveHint` annotations.
- 15, sensible defaults, few required parameters, and official SDKs in at least two languages.

Models are read for tool use, structured output, prompt caching, context length, batch and SDKs. Frameworks for how much code and how many defaults a tool-calling agent with MCP needs.

## 4. Payments & pricing, 0 out of 100, up to 12.5 more on the total

Why it scored 0: Nothing to buy. No machine payment protocol when it ran (0). The Vertex AI pricing page still lists Imagen 4 at $0.02 to $0.06 an image three months after discontinuation, which is a price for a product you can't call (0). No free tier (0). Human sign-up and billing account (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-payments):

The published rubric, also on the [x402 page](https://www.anchorterminal.com/x402/).

- 40, a machine payment protocol (x402, MPP or L402) on the tool's own endpoints. 10 to 30 when it covers only some endpoints or only goes through a third party, and the note says which.
- 20, per-call or per-unit pricing published without a login. 10 for public plan-only pricing, 0 for "contact sales" or prices behind a login.
- 20, a free tier or trial that doesn't need a card.
- 20, autonomous onboarding, meaning an agent can get access without a person signing up in a browser (keyless use, x402, a programmatic key API).

Payment platforms and agent wallets rarely charge for their own API over a machine protocol, so the first line has steps for them, and the highest one that applies counts. 40 when x402, MPP or L402 runs on all their own endpoints, 30 when it runs on part of their own API, 25 when their merchants can accept one, 20 for running a facilitator, 15 for paying as a buyer, and 0 when the only protocol is their own. Merchant acceptance sits above a facilitator because the platform's own customers can charge agents through it, while a facilitator settles for sellers who wire up the protocol themselves. The counter-argument (a facilitator does more for the protocol as a whole) has a point. Each note says which step applied.

Open-source software you run yourself is scored on its hosted or paid option if it has one. A free, self-hosted package with nothing to buy gets 20, 20 and 20 for the last three lines, and 0 to 40 for the first only if it ships a payment protocol.

## 5. Schema & documentation, 25 out of 100, up to 12.2 more on the total

Why it scored 25: What's left is documentation. No OpenAPI or other contract for the retired endpoints (0) and no llms.txt found for them (0). The Gemini API Imagen page is now a migration notice naming the replacement models and the three changes needed (5). The parameter reference is gone (0). Migration steps but no worked example on the page (5). Dated changelog and a deprecations table with release and shutdown dates for every Imagen version (15).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-schema):

APIs and MCP servers.

- 25, a machine-readable contract (a public OpenAPI file or similar; for MCP, typed JSON Schema inputs on every tool).
- 10, llms.txt or Markdown docs served for agents.
- 0 to 20, descriptions that say what a tool is for, when to use it and when not to, read from the tool definitions in the source or the API reference.
- 0 to 15, typed inputs with enums, constraints and required fields, and no free-form JSON blobs.
- 0 to 15, examples and documented error responses.
- 15, versioning and a public changelog.

Models are read from the API reference, the OpenAPI file, llms.txt, the structured-output and tool-use docs and the model cards. Frameworks from docs a model can follow, typed interfaces, examples and the API reference.

## 6. Maintenance & community, 5 out of 100, up to 8.3 more on the total

Why it scored 5: No release since Imagen 4 went GA on 14 August 2025 (0) and none planned (0). Notice periods were 98 days on Vertex AI (announced 24 March 2026, discontinued 30 June 2026) and 63 days on the Gemini API (announced 15 June 2026, shut down 17 August 2026), short for a model that had been GA for under a year. A public forum thread about the loss of mask-based editing in imagen-3.0-capability-001 shows no reply from Google. The public changelog still counts (5). Official SDKs no longer reach the model (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-maintenance):

- 0 to 30, time since the last release, or the last published model or API change for a closed service. 30 within 30 days, 20 within 90, 10 within 180, 0 older.
- 20, at least three releases or dated changelog entries in the last 90 days.
- 0 to 25, responsiveness. Issues and pull requests answered on GitHub (the open issues and how recent the replies are). For closed services, a public changelog and a support or community channel that answers, 0 to 15.
- 15, presence in the official MCP registry under a verified namespace (MCP servers), or current official SDKs (APIs and models).
- 10, package health, current dependencies and CI.

Models are read for deprecation notice periods and model churn rather than release counts.

## 7. Transparency & trust, 65 out of 100, up to 3.1 more on the total

Made of editorial 30, provenance 100.

Why it scored 65: Closed model under Google's API terms (15). We didn't re-check retention statements for a product that no longer takes traffic, so none counted (0). Deprecation notices carry dates on both platforms and name replacements, and Vertex release notes date every Imagen removal back to 2025, but the Vertex pricing page still advertises the retired rates (15). Subprocessors and data locations not checked for a retired product (0).

The checklist (https://www.anchorterminal.com/benchmark/#checklist-transparency):

- 0 to 30, source availability and licence clarity. 30 for open source under an OSI licence, 15 for closed with clear terms, 0 for unclear terms.
- 0 to 30, data handling and retention statements that agree with each other (privacy policy, DPA, retention periods, subprocessors).
- 0 to 20, a deprecation policy or notices with dates.
- 0 to 20, telemetry disclosed with an opt-out (local software), or subprocessors and data locations disclosed (hosted).

The other half of Transparency and trust is the provenance score, computed from checked facts (below). The category score is the mean of the two.

## Deductions

Each comes off the total. A fixed and documented problem counts for less at the next check.

- Since 2026-06-30 the Vertex AI generative AI pricing page still lists Imagen 4, Imagen 4 Fast and Imagen 4 Ultra at $0.02 to $0.06 an image with no discontinuation note, three months after the endpoints were discontinued (https://cloud.google.com/vertex-ai/generative-ai/pricing, seen 2026-10-01). -3, the low end, because the model pages and release notes do carry the date.

## What we couldn't check

What we couldn't read counted as absent. Publishing it on a page a plain HTTP fetch can read (not only in a browser) lets the next check count it.

- We couldn't call the endpoints to confirm the exact error a retired Imagen model name returns today on each platform.
- The listing's note that Vertex lists C2PA as not supported was wrong for Imagen 4 and Fast. Corrected in patch.notable and patch.details.

## Weaknesses

- Discontinued. Calls to imagen model names fail on both the Gemini API and Vertex AI
- Notice was 63 days on the Gemini API and 98 days on Vertex AI, for a model GA since August 2025
- Mask-based editing from imagen-3.0-capability-001 has no Google replacement
- The Vertex AI pricing page still lists Imagen 4 rates with no discontinuation note

## What costs an agent a turn today

The notes we give agents before they call it. Each one is a workaround an agent shouldn't need.

- Replace `client.models.generate_images` with `client.models.generate_content` and a `gemini-3.1-flash-image` model
- Read images from the response content parts, not from `generated_images`
- Don't budget from the Vertex Imagen price rows, they describe a retired product
- If the job needs a mask-based inpaint, use another vendor's fill endpoint, since Gemini image editing is prompt-based

## What the review panel asked for

- Flag retired prices
- remove retired rates from the Vertex pricing page

## When it's done

Send what changed and where it's published as a dispute (https://www.anchorterminal.com/builders/#disputes, or `POST https://www.anchorterminal.com/api/v1/contact` with `"kind": "dispute"`). Disputes are answered in public, and the listing is checked again by the same checklist. Paying for an audit or a listing claim changes nothing here.