feat(ai-openai): accept gpt-image-2.5-flare and gpt-image-2.5-sunburst

[AlexDemzz]

You can now use gpt-image-2.5-flare and gpt-image-2.5-sunburst with openaiImage(). Today both ids fail the type check, and at run time the size check throws Unknown image model before any request goes out. This PR adds both models with the sizes and quality levels that OpenAI documents, including the new xhigh and max quality levels.

🎯 Changes

• model-meta.ts: add both models to OPENAI_IMAGE_MODELS. The token prices are the same as gpt-image-2.
• image-provider-options.ts: sizes 1024x1024, 1536x1024, 1024x1536 and auto. quality is low | medium | high | xhigh | max | auto. background is allowed.
• adapters/image.ts: up to 16 edit source images, the same as the other gpt-image models. The modelOptions spread is cast, because the OpenAI SDK (6.41.0) quality type does not list xhigh / max yet.
• Docs: rows added to the size, edit and count tables in docs/media/image-generation.md.

Sources: gpt-image-2.5-flare, gpt-image-2.5-sunburst, image generation guide, changelog (2026-09-08).

✅ Checklist

• I have followed the steps in the Contributing guide.
• I have tested code changes locally with pnpm run test:pr, or these tests do not apply to this pull request.
• I fully understand the code in this pull request, including any code generated with AI assistance.
• Docs: I updated docs/ for this change, or this change is not user-facing.
• Changeset: I added a changeset (pnpm changeset), or this PR does not change a published package.

🚀 Release Impact

• This change affects published code, and I have generated a changeset.
• This change is docs/CI/dev-only (no release).

Testing

Commands run

• pnpm test:pr: passed.
• pnpm --filter @tanstack/ai-e2e exec playwright test tests/openai-image-2-5-models.spec.ts tests/image-gen.spec.ts tests/image-to-image.spec.ts: 8 passed. I did not run the full E2E suite.
• The new unit test and the new E2E spec both fail on main with Unknown image model: gpt-image-2.5-flare.

Manual test

1. Run pnpm --filter @tanstack/ai-openai exec vitest run tests/image-adapter.test.ts.
2. Look for sends gpt-image-2.5-flare with a listed size and the xhigh quality (and the sunburst case). Both pass.

How this PR makes testing easy

• Unit test: packages/ai-openai/tests/image-adapter.test.ts, one case per model.
• E2E: testing/e2e/tests/openai-image-2-5-models.spec.ts generates one image on each model through aimock.

Risk / rollback

Low. The change only adds model ids. Existing models keep the same behavior. OpenAI does not publish a separate edit input cap for the 2.5 models, so 16 is the gpt-image family cap. The API returns its own error if the cap is lower. Revert the PR to undo.

Public API change

Before

openaiImage('gpt-image-2.5-flare') // type error; throws "Unknown image model" at run time

After

await generateImage({
  adapter: openaiImage('gpt-image-2.5-flare'),
  prompt: 'A cat wearing a hat',
  size: '1536x1024',
  modelOptions: { quality: 'max' },
})

🤖 Generated with Claude Code

Summary by CodeRabbit

• New Features
  • Added support for OpenAI’s gpt-image-2.5-flare and gpt-image-2.5-sunburst models for image generation and image editing.
  • Both models support up to 16 source images for editing, along with xhigh and max quality settings.
• Documentation
  • Updated the image-generation guide with supported model sizes, image counts, quality settings, and editing capabilities.

[coderabbitai]

Navigate logical layers of code changes, visualize relationships, and explore their blast radius.

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

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📥 Commits

Reviewing files that changed from the base of the PR and between d632d41 and 0021811.

📒 Files selected for processing (10)

• .changeset/openai-gpt-image-2-5.md
• docs/config.json
• docs/media/image-generation.md
• packages/ai-openai/src/adapters/image.ts
• packages/ai-openai/src/image/image-provider-options.ts
• packages/ai-openai/src/model-meta.ts
• packages/ai-openai/tests/image-adapter.test.ts
• testing/e2e/src/routeTree.gen.ts
• testing/e2e/src/routes/api.openai-image-2-5-models.ts
• testing/e2e/tests/openai-image-2-5-models.spec.ts

Included review availability: This review used your included allowance. Your plan provides up to 8 included reviews per hour; 7 remain after this review.

---

📝 Walkthrough

Walkthrough

The OpenAI image adapter now supports gpt-image-2.5-flare and gpt-image-2.5-sunburst. The change adds their provider options, model metadata, generation and editing support, documentation, and unit and end-to-end tests.

Changes

GPT Image 2.5 models

Layer / File(s)	Summary
Model contracts and registration packages/ai-openai/src/image/image-provider-options.ts, packages/ai-openai/src/model-meta.ts	Adds provider-option types, size and background validation, model metadata, and model-list entries for both models.
Image request support and reference material packages/ai-openai/src/adapters/image.ts, packages/ai-openai/tests/image-adapter.test.ts, docs/media/image-generation.md, docs/config.json, .changeset/openai-gpt-image-2-5.md	Adds generation request handling and edit-image limits for both models. Tests check generation arguments and returned image data. The guide and changeset describe model settings and support.
E2E route and coverage testing/e2e/src/routes/api.openai-image-2-5-models.ts, testing/e2e/src/routeTree.gen.ts, testing/e2e/tests/openai-image-2-5-models.spec.ts	Adds a POST route that generates an image with each model and a test that checks for one image and no reported error.

Priority: ➖ Normal

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Feature

Suggested reviewers: tombeckenham

Merge Risk: ⚪ Minimal · up to 00218

No actionable issue remains in the reviewed model support, request handling, or tests; the PR is mergeable after normal checks.

Security Architecture Review

Security architecture risk: 🟡 Moderate · up to 00218

The change expands an image-generation integration and introduces a test endpoint. Normal testing uses fixed inputs and a local mock service, but the endpoint’s deployment constraints have not been demonstrated.

Retained concerns

• Medium · security · inferred: The new unauthenticated E2E POST endpoint makes two downstream image-generation attempts per request, while mock confinement is a default rather than an enforced boundary: its target is selected by the environment-overridable LLMOCK_URL. If this test server is exposed with a credential-translating or paid compatible target, repeated calls could consume privileged downstream resources. Current deployment exposure and target policy are unproven.

Security review details

Security Blast Radius

• observed — The added test route is registered as a POST endpoint and executes one image-generation operation for each of two fixed model identifiers on every request.

Security Findings and Attack Paths

• inferred — There is no verified direct-provider billing or privilege-escalation path: the route uses a fixed dummy key and local mock target by default. Exposure becomes material only if an environment exposes the E2E application and redirects LLMOCK_URL to a service that accepts or translates that credential.

Trust Boundaries and Controls

• observed — The route contains no request authentication or caller-controlled input handling. The downstream target is operator-controlled through LLMOCK_URL, with a loopback mock default; repository evidence does not provide a policy that constrains overrides or deployment reachability.
• observed — Provider input controls validate image size, reject unsupported model-size combinations, limit source images for editing, and reject unsupported mask arrangements before the downstream edit call.

Resilience and Maintainability Implications

• observed — Per-model errors are captured into the E2E response and adapter errors are sanitized before logging, but the handler returns HTTP 200 after downstream failures; no route-specific authentication, quota, rate-limit, or abuse-monitoring control is evidenced.

Hardening Proposals

• proposed — Ensure environments capable of serving the E2E application restrict the route to test-only access and constrain its downstream target to approved mock infrastructure; if broader exposure is intended, apply authentication and request-volume controls appropriate to its downstream resource cost.

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description check	✅ Passed	The description is complete and aligned with the template. It explains the change, documents testing, addresses risk and rollback, includes the required checklist, and records release impact.
Title check	✅ Passed	The title clearly and concisely identifies the primary change: support for the two new OpenAI image models in ai-openai.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 1 functions across 7 files. (3 skipped: 3 …
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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☁️ Nx Cloud last updated this comment at 2026-09-27 10:58:00 UTC

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commit: 0021811