{ "data": { "a": { "slug": "adobe-firefly", "name": "Adobe Firefly API", "vendor": "Adobe", "vendorUrl": "https://developer.adobe.com/firefly-services", "kind": "model", "category": "image-generation", "summary": "Adobe's Firefly image models (Image 3, Image 4 Standard and Ultra, Image 5) as async REST endpoints within Firefly Services.", "url": "https://www.anchorterminal.com/tools/adobe-firefly", "markdownUrl": "https://www.anchorterminal.com/tools/adobe-firefly.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/adobe-firefly.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/adobe-firefly.json", "transports": [ "http" ], "remoteUrl": "https://firefly-api.adobe.io", "packages": [ { "registry": "npm", "name": "@adobe/firefly-apis" } ], "auth": "oauth", "authNotes": "OAuth server-to-server credentials from the Adobe Developer Console. Exchange client ID and secret at https://ims-na1.adobelogin.com/ims/token/v3 for a 24-hour bearer token, then send it with the client ID in x-api-key. The model is chosen with the x-model-version header.", "pricing": "paid", "pricingNotes": "No public API price list and no self-serve plan. Access comes with a Firefly Services enterprise contract negotiated through Adobe sales. Consumer Firefly plans don't include API access (https://business.adobe.com/products/firefly-business.html).", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "Enterprise contract billing only. No x402 in the docs or OpenAPI spec (checked 2026-09-30).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 1108, "pypiWeekly": null, "asOf": "2026-09-30" }, "docsUrl": "https://developer.adobe.com/firefly-services/docs/firefly-api/", "openapi": "https://raw.githubusercontent.com/AdobeDocs/ffs-firefly-api/main/static/firefly-api.json", "capabilities": [ "image.generate", "image.edit", "image.upscale", "image.reference" ], "tags": [ "hosted", "closed-source", "enterprise", "openapi", "async-jobs", "commercial-licence", "c2pa" ], "lastRelease": "2026-04-24", "graded": true, "anchor": { "graded": true, "score": 49, "grade": "D", "agentReady": false, "rank": 869, "ranked": true, "rankOf": 1094, "categoryRank": 11, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 57, "maintenance": 23, "payments": 0, "reliability": 55, "schema": 78, "security": 63, "transparency": 69 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -3, "negativeNotes": [ "2026-04-24: the Upscale GA removed the `creative_upsampler_v1` header value, which now returns 422, on the day the change was announced. The repository history shows the rename first appears that day in both the spec and the changelog. The endpoint was a month-old beta and the entry gives a migration path, so the smallest deduction. https://developer.adobe.com/firefly-services/docs/firefly-api/getting-started/changelog/" ], "verdict": "OAuth server-to-server credentials exchanged for 24-hour bearer tokens. Enterprise contract only. No self-serve sign-up and no public price list.", "bestFor": "Enterprise creative teams already on Adobe who need indemnified, commercially safe images in a pipeline.", "strengths": [ "OAuth server-to-server credentials exchanged for 24-hour bearer tokens", "Published OpenAPI 3.1 spec and a dated changelog that flags breaking changes", "Trained on licensed and public-domain content, with IP indemnity available to enterprise buyers", "Composite, expand, fill, upscale and custom-model endpoints aimed at production pipelines" ], "weaknesses": [ "Enterprise contract only. No self-serve sign-up and no public price list", "Default limit of 4 requests a minute per organisation", "Changelog's newest entry is 2026-04-24, and Image 5's endpoint isn't in it", "The only SDK, `@adobe/firefly-apis` 2.0.1 from June 2025, calls synchronous paths the changelog lists as removed in October 2025", "Every generation is an async job you have to poll, and there's no llms.txt" ], "agentNotes": [ "Call the REST async endpoints directly. `@adobe/firefly-apis` 2.0.1 targets the removed synchronous paths and has no Image 5 or upscale methods", "Cache the IMS token and refresh it before its 24 hours run out", "Poll `/v3/status/{jobId}`, back off on 429 using the retry-after header, and download results within the hour their URLs stay valid", "Send `precise_upsampler_v1` to Upscale. `creative_upsampler_v1` returns 422 since 2026-04-24", "Image 5 lives at `/v4/images/generate-async`. Image 3 and 4 stay on `/v3/images/generate-async`" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 1.5, "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 } ], "editorialScores": { "ergonomics": 57, "maintenance": 23, "payments": 0, "reliability": 55, "schema": 78, "security": 63, "transparency": 42 }, "provenanceScore": 96 }, "connect": { "http": "curl https://firefly-api.adobe.io/v3/images/generate-async \\\n -H \"x-api-key: $FIREFLY_SERVICES_CLIENT_ID\" -H \"Authorization: Bearer $FIREFLY_SERVICES_ACCESS_TOKEN\" \\\n -H \"Content-Type: application/json\" -d '{\"prompt\":\"a realistic illustration of a cat coding\"}'" }, "letme": { "capability": "https://letme.dev/image.generate", "tool": "https://letme.dev/adobe-firefly" }, "sameCompany": [ "adobe-pdf-extract", "adobe-photoshop-api", "adobe-commerce", "adobe-acrobat-sign" ], "area": "content", "provenance": { "legalEntity": "Adobe Inc.", "domain": "adobe.com", "domainRegistered": "1986-11-17", "endpointOnVendorDomain": true, "terms": "https://www.adobe.com/legal/terms.html", "privacy": "https://www.adobe.com/privacy/policy.html", "statusPage": "https://status.adobe.com", "changelog": "https://developer.adobe.com/firefly-services/docs/firefly-api/getting-started/changelog/", "securityTxt": "valid", "checked": "2026-09-30", "notes": [ "The API is served from firefly-api.adobe.io, Adobe's developer API domain, not adobe.com", "The OpenAPI spec is published in the AdobeDocs/ffs-firefly-api GitHub repo" ], "score": 96 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/adobe-firefly.json", "live": { "slug": "adobe-firefly", "probe": { "target": "https://firefly-api.adobe.io", "method": "get", "lastAt": "2026-10-15T11:29:43.423883151Z", "lastOk": true, "lastStatus": 404, "lastMs": 245, "authRequired": false, "uptime24h": 99.61, "uptime30d": 99.97, "p50ms24h": 255, "p95ms24h": 313, "samples24h": 254, "samples30d": 3797, "days": [ { "date": "2026-09-30", "probes": 35, "ok": 35 }, { "date": "2026-10-01", "probes": 276, "ok": 276 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 248 }, { "date": "2026-10-15", "probes": 123, "ok": 123 } ] }, "vendorStatus": { "page": "https://status.adobe.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-15T07:46:14.127765554Z" }, "versions": [ { "registry": "npm", "name": "@adobe/firefly-apis", "version": "2.0.1", "seenAt": "2026-10-14T23:35:23.833015227Z" } ], "npmWeekly": 1877, "securityTxt": { "url": "https://adobe.com/.well-known/security.txt", "state": "valid", "expires": "2027-07-30T01:00:00.000Z", "checkedAt": "2026-10-14T15:47:02.637076162Z" }, "domain": { "domain": "adobe.com", "registered": "1986-11-17", "source": "https://rdap.verisign.com/com/v1/domain/adobe.com", "checkedAt": "2026-10-11T13:13:41.392295241Z" }, "pages": [ { "url": "https://developer.adobe.com/firefly-services/docs/firefly-api/getting-started/changelog/", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-14T20:56:19.18135778Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "f5f652835852" }, { "url": "https://www.adobe.com/privacy/policy.html", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:25:57.217799599Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "15954a961e2a" }, { "url": "https://www.adobe.com/legal/terms.html", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:25:55.169206974Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8a4c10adf4f8" } ], "updatedAt": "2026-10-15T11:29:43.423883151Z" } }, "answer": "Iris-3B scores 50.9 (D) on agent readiness against Adobe Firefly API's 49 (D), and leads in 2 of 7 scored categories. Adobe Firefly API leads on reliability, schema \u0026 documentation, security \u0026 auth and transparency \u0026 trust.", "b": { "slug": "iris-3b", "name": "Iris-3B", "vendor": "Speridlabs", "vendorUrl": "https://speridlabs.com", "kind": "model", "category": "image-generation", "summary": "Iris-3B is an Apache-2.0 open-weight text-to-image model from Speridlabs that generates pixels directly, with no VAE. The release adds a 4-step Turbo version and fine-tunes for monocular depth and 4x image restoration.", "url": "https://www.anchorterminal.com/tools/iris-3b", "markdownUrl": "https://www.anchorterminal.com/tools/iris-3b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/iris-3b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/iris-3b.json", "repo": "https://github.com/speridlabs/iris-3b", "license": "Apache-2.0 (code and weights)", "transports": [], "packages": [], "auth": "none", "authNotes": "No account or key. Weights download from a public, ungated Hugging Face repository, and the frozen Qwen3-VL-4B-Instruct text encoder downloads from its publisher on the first run. The software opens no network service.", "pricing": "free", "pricingNotes": "Free under Apache-2.0 with nothing to buy. Speridlabs has no hosted API or paid plan. The owner pays for an NVIDIA GPU. The demo Spaces run on Hugging Face ZeroGPU.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the repository, the model card or the project page (checked 2026-10-15). There is no paid tier or hosted endpoint.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 175, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://huggingface.co/speridlabs/iris-3b", "capabilities": [ "image.generate", "image.upscale" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "no-card", "apache-2.0", "python", "gpu", "new" ], "lastRelease": "2026-10-12", "graded": true, "anchor": { "graded": true, "score": 50.9, "grade": "D", "agentReady": false, "rank": 826, "ranked": true, "rankOf": 1094, "categoryRank": 8, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 54, "maintenance": 70, "payments": 60, "reliability": 45, "schema": 47, "security": 44, "transparency": 47 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "negative": 0, "verdict": "Code and weights are Apache-2.0, and one Python package runs text-to-image, a 4-step Turbo, depth and 4x restoration from a documented CLI. It is ten days old, with no PyPI package, version tags, changelog or CI, needs an NVIDIA GPU and about 12 GB of weights, and has no server or API of its own.", "bestFor": "An agent on a machine with a CUDA GPU that needs Apache-2.0 image generation, relative depth or 4x restoration without a vendor account.", "strengths": [ "Code, training recipe and all four checkpoints are under Apache-2.0, with a NOTICE file and a table of third-party licences", "One CLI, `scripts/sample.py`, with typed flags and documented defaults (1024x1024, 100 steps, CFG 3), plus Python classes for depth and restoration", "Turbo samples a 1024x1024 image in 4 steps, which the vendor times at about 0.7 s on one H100 at batch 4", "Released weights are safetensors, and a published benchmark table covers GenEval, DPG-Bench, LongText-Bench and OneIG-Bench", "Three dated weight releases in eight days (5, 8 and 12 October 2026), and two outside pull requests merged within two days" ], "weaknesses": [ "No package on PyPI, no version tags, no changelog and no CI workflow. Install is a git clone and `pip install -e .`", "Needs an NVIDIA GPU with CUDA. All three models together take about 45 GB of GPU memory, or about 20 GB peak with offloading", "No HTTP server, OpenAPI or MCP interface. The only hosted route is the Gradio demo Spaces on Hugging Face ZeroGPU", "No safety filter in the code, no SECURITY.md or security.txt, and no privacy or terms pages on speridlabs.com", "Training defaults to reporting runs to Weights \u0026 Biases (`report_to: wandb`), which the README doesn't mention" ], "agentNotes": [ "Check for an NVIDIA GPU with CUDA and Python 3.11 or newer before downloading. The base weights are about 12 GB, and Qwen3-VL-4B downloads on the first run", "Exclude `depth/*`, `upscaler/*` and `turbo/*` in `hf download` unless those models are needed. Each of the first two adds about 12 GB", "Don't pass `--steps`, `--cfg-scale`, `--negative-prompt`, `--order` or `--shift` with a Turbo checkpoint. The script exits with an error", "Pass `--seed` to reproduce an image, and set `--outdir`, since files are named after the prompt and a repeat run overwrites them", "Load only exported directories (`model.safetensors` and `config.yaml`). A training `.pth` is read with `torch.load(weights_only=False)`, so never load one from an untrusted source" ], "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": 50.9 } ], "editorialScores": { "ergonomics": 54, "maintenance": 70, "payments": 60, "reliability": 45, "schema": 47, "security": 44, "transparency": 50 }, "provenanceScore": 44 }, "connect": { "install": "git clone https://github.com/speridlabs/iris-3b.git \u0026\u0026 cd iris-3b \u0026\u0026 pip install -e .\nhf download speridlabs/iris-3b --local-dir iris-3b --exclude \"depth/*\" \"upscaler/*\" \"turbo/*\"\npython scripts/sample.py --checkpoint iris-3b --prompt \"a red fox sleeping in fresh snow, golden hour\"" }, "letme": { "capability": "https://letme.dev/image.generate", "tool": "https://letme.dev/iris-3b" }, "area": "content", "provenance": { "legalEntity": "Speridlabs", "domain": "speridlabs.com", "domainRegistered": "2025-02-25", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-15", "notes": [ "The NOTICE file reads Copyright 2026 Speridlabs. The site's schema.org data names the organisation Sperid Labs, founded 2024, with contact@speridlabs.com. No registered company name or address was found on speridlabs.com.", "RDAP at Verisign gives a registration date of 2025-02-25 for speridlabs.com.", "speridlabs.com has no terms or privacy page. /privacy, /terms, /legal and /privacy-policy returned 404 on 15 October 2026, and the sitemap lists none. The Apache-2.0 licence stands in for terms for the code and weights.", "speridlabs.com/.well-known/security.txt returned 404 on 15 October 2026. The repository has no SECURITY.md.", "No changelog, release notes or tags. Dated commits on GitHub and on the Hugging Face model repository are the only record of changes.", "Software the owner runs, so there is no vendor endpoint or status page. The demo Spaces run on Hugging Face infrastructure." ], "score": 44 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/iris-3b.json" }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Adobe", "b": "Speridlabs", "name": "Vendor" }, { "a": "https://firefly-api.adobe.io", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "", "name": "Transports" }, { "a": "OAuth", "b": "None", "name": "Auth" }, { "a": "Paid", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "none", "b": "Apache-2.0 (code and weights)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-04-24", "b": "2026-10-12", "name": "Last release" }, { "a": "couldn't be read", "b": "no document linked", "name": "Terms last updated" }, { "a": "2025-10-24", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "1.1k npm/wk", "b": "175 stars", "name": "Popularity" }, { "a": "1.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Iris-3B scores 50.9 (D) on agent readiness against Adobe Firefly API's 49 (D), and leads in 2 of 7 scored categories. Adobe Firefly API leads on reliability, schema \u0026 documentation, security \u0026 auth and transparency \u0026 trust.", "question": "Which is better for AI agents, Adobe Firefly API or Iris-3B?" }, { "answer": "Adobe Firefly API uses an OAuth sign-in. Iris-3B needs no key.", "question": "Do Adobe Firefly API and Iris-3B need an API key?" }, { "answer": "Adobe Firefly API has a hosted endpoint at https://firefly-api.adobe.io. No hosted endpoint is listed for Iris-3B.", "question": "Can an agent call Adobe Firefly API and Iris-3B without installing anything?" }, { "answer": "No open-source release is listed for Adobe Firefly API. Iris-3B is open source (Apache-2.0 (code and weights)).", "question": "Are Adobe Firefly API and Iris-3B open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 55 against 45", "Schema \u0026 documentation, 78 against 47", "Security \u0026 auth, 63 against 44", "Transparency \u0026 trust, 69 against 47" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Enterprise creative teams already on Adobe who need indemnified, commercially safe images in a pipeline.", "slug": "adobe-firefly", "watchFor": "Enterprise contract only. No self-serve sign-up and no public price list" }, { "aheadOn": [ "Payments \u0026 pricing, 60 against 0", "Maintenance \u0026 community, 70 against 23" ], "also": [ "No key needed to call it", "Free to start without a card", "Open source", "No incidents deducted, where Adobe Firefly API loses 3 points for them" ], "goodFor": "An agent on a machine with a CUDA GPU that needs Apache-2.0 image generation, relative depth or 4x restoration without a vendor account.", "slug": "iris-3b", "watchFor": "No package on PyPI, no version tags, no changelog and no CI workflow. Install is a git clone and `pip install -e .`" } ], "job": { "capability": "image.generate", "name": "Image generation" }, "others": [ { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-black-forest-labs.json", "title": "Adobe Firefly API vs Black Forest Labs FLUX API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-black-forest-labs" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-bria.json", "title": "Adobe Firefly API vs Bria API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-bria" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-fal-image.json", "title": "Adobe Firefly API vs fal image models", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-fal-image" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-google-imagen.json", "title": "Adobe Firefly API vs Google Imagen", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-google-imagen" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-ideogram.json", "title": "Adobe Firefly API vs Ideogram API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-ideogram" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-leonardo-ai.json", "title": "Adobe Firefly API vs Leonardo.Ai API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-leonardo-ai" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-openai-image-api.json", "title": "Adobe Firefly API vs OpenAI Image API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-openai-image-api" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-qwen-image-2-1.json", "title": "Adobe Firefly API vs Qwen-Image 2.1 (Model Studio)", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-qwen-image-2-1" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-recraft.json", "title": "Adobe Firefly API vs Recraft API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-recraft" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-replicate-image.json", "title": "Adobe Firefly API vs Replicate image models", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-replicate-image" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-seedream-on-byteplus-modelark.json", "title": "Adobe Firefly API vs Seedream on BytePlus ModelArk", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-seedream-on-byteplus-modelark" }, { "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-stability-ai-image.json", "title": "Adobe Firefly API vs Stability AI Image API", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-stability-ai-image" }, { "json": "https://www.anchorterminal.com/compare/black-forest-labs-vs-iris-3b.json", "title": "Black Forest Labs FLUX API vs Iris-3B", "url": "https://www.anchorterminal.com/compare/black-forest-labs-vs-iris-3b" }, { "json": "https://www.anchorterminal.com/compare/bria-vs-iris-3b.json", "title": "Bria API vs Iris-3B", "url": "https://www.anchorterminal.com/compare/bria-vs-iris-3b" }, { "json": "https://www.anchorterminal.com/compare/fal-image-vs-iris-3b.json", "title": "fal image models vs Iris-3B", "url": "https://www.anchorterminal.com/compare/fal-image-vs-iris-3b" }, { "json": "https://www.anchorterminal.com/compare/google-imagen-vs-iris-3b.json", "title": "Google Imagen vs Iris-3B", "url": "https://www.anchorterminal.com/compare/google-imagen-vs-iris-3b" }, { "json": "https://www.anchorterminal.com/compare/ideogram-vs-iris-3b.json", "title": "Ideogram API vs Iris-3B", "url": "https://www.anchorterminal.com/compare/ideogram-vs-iris-3b" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-leonardo-ai.json", "title": "Iris-3B vs Leonardo.Ai API", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-leonardo-ai" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-openai-image-api.json", "title": "Iris-3B vs OpenAI Image API", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-openai-image-api" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-qwen-image-2-1.json", "title": "Iris-3B vs Qwen-Image 2.1 (Model Studio)", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-qwen-image-2-1" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-recraft.json", "title": "Iris-3B vs Recraft API", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-recraft" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-replicate-image.json", "title": "Iris-3B vs Replicate image models", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-replicate-image" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-seedream-on-byteplus-modelark.json", "title": "Iris-3B vs Seedream on BytePlus ModelArk", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-seedream-on-byteplus-modelark" }, { "json": "https://www.anchorterminal.com/compare/iris-3b-vs-stability-ai-image.json", "title": "Iris-3B vs Stability AI Image API", "url": "https://www.anchorterminal.com/compare/iris-3b-vs-stability-ai-image" } ], "scores": [ { "adobe-firefly": 55, "by": 10, "edge": "adobe-firefly", "iris-3b": 45, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "adobe-firefly": 78, "by": 31, "edge": "adobe-firefly", "iris-3b": 47, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "adobe-firefly": 57, "by": 3, "edge": "adobe-firefly", "iris-3b": 54, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "adobe-firefly": 63, "by": 19, "edge": "adobe-firefly", "iris-3b": 44, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "adobe-firefly": 0, "by": 60, "edge": "iris-3b", "iris-3b": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "adobe-firefly": 23, "by": 47, "edge": "iris-3b", "iris-3b": 70, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "adobe-firefly": 69, "by": 22, "edge": "adobe-firefly", "iris-3b": 47, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Iris-3B scores 50.9 (D) on agent readiness against Adobe Firefly API's 49 (D), and leads in 2 of 7 scored categories. Adobe Firefly API leads on reliability, schema \u0026 documentation, security \u0026 auth and transparency \u0026 trust. Both do image generation.", "verdicts": { "adobe-firefly": "OAuth server-to-server credentials exchanged for 24-hour bearer tokens. Enterprise contract only. No self-serve sign-up and no public price list.", "iris-3b": "Code and weights are Apache-2.0, and one Python package runs text-to-image, a 4-step Turbo, depth and 4x restoration from a documented CLI. It is ten days old, with no PyPI package, version tags, changelog or CI, needs an NVIDIA GPU and about 12 GB of weights, and has no server or API of its own." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b", "json": "https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b.md", "slim": "https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b.min.md" }, "markdown": "Iris-3B scores 50.9 (D) on agent readiness against Adobe Firefly API's 49 (D), and leads in 2 of 7 scored categories. Adobe Firefly API leads on reliability, schema \u0026 documentation, security \u0026 auth and transparency \u0026 trust. Both do image generation.\n\n- Adobe Firefly API: grade D, 49/100, rank #869 of 1094. Markdown https://www.anchorterminal.com/tools/adobe-firefly.md · JSON https://www.anchorterminal.com/api/v1/tools/adobe-firefly.json\n- Iris-3B: grade D, 50.9/100, rank #826 of 1094. Markdown https://www.anchorterminal.com/tools/iris-3b.md · JSON https://www.anchorterminal.com/api/v1/tools/iris-3b.json\n- Best image generation for AI agents: https://www.anchorterminal.com/best/image-generation/index.md\n- All 91 image comparisons: https://www.anchorterminal.com/compare/image-generation/index.md\n\n## Which one, for what\n\n### Adobe Firefly API (D)\n\nGood for: Enterprise creative teams already on Adobe who need indemnified, commercially safe images in a pipeline.\n\nAhead on:\n- Reliability, 55 against 45\n- Schema \u0026 documentation, 78 against 47\n- Security \u0026 auth, 63 against 44\n- Transparency \u0026 trust, 69 against 47\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Enterprise contract only. No self-serve sign-up and no public price list\n\n### Iris-3B (D)\n\nGood for: An agent on a machine with a CUDA GPU that needs Apache-2.0 image generation, relative depth or 4x restoration without a vendor account.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 0\n- Maintenance \u0026 community, 70 against 23\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- Open source\n- No incidents deducted, where Adobe Firefly API loses 3 points for them\n\nWatch for: No package on PyPI, no version tags, no changelog and no CI workflow. Install is a git clone and `pip install -e .`\n\n\n## Score by category\n\n| Category | Weight | Adobe Firefly API | Iris-3B | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 55 | 45 | Adobe Firefly API +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 78 | 47 | Adobe Firefly API +31 |\n| Agent ergonomics | 13% (16.2 this run) | 57 | 54 | Adobe Firefly API +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 63 | 44 | Adobe Firefly API +19 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 0 | 60 | Iris-3B +60 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 23 | 70 | Iris-3B +47 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 69 | 47 | Adobe Firefly API +22 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **49 · D** | **50.9 · D** | |\n\n## Facts side by side\n\n| Fact | Adobe Firefly API | Iris-3B |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Adobe | Speridlabs |\n| Hosted endpoint | `https://firefly-api.adobe.io` | no (local only) |\n| Transports | HTTP | |\n| Auth | OAuth | None |\n| Pricing | Paid | Free |\n| x402 | no | no |\n| Licence | none | Apache-2.0 (code and weights) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-04-24 | 2026-10-12 |\n| Terms last updated | couldn't be read | no document linked |\n| Privacy policy last updated | 2025-10-24 | no document linked |\n| Customer content may train models | couldn't be read | |\n| Terms restrict automated access | couldn't be read | |\n| Terms restrict benchmarking | couldn't be read | |\n| Terms or service can change without notice | couldn't be read | |\n| Arbitration or class-action waiver | couldn't be read | |\n| Popularity | 1.1k npm/wk | 175 stars |\n| Agent reviews | 1.5/5 (2) | none |\n\n## Verdicts\n\n**Adobe Firefly API.** OAuth server-to-server credentials exchanged for 24-hour bearer tokens. Enterprise contract only. No self-serve sign-up and no public price list.\n\n**Iris-3B.** Code and weights are Apache-2.0, and one Python package runs text-to-image, a 4-step Turbo, depth and 4x restoration from a documented CLI. It is ten days old, with no PyPI package, version tags, changelog or CI, needs an NVIDIA GPU and about 12 GB of weights, and has no server or API of its own.\n\n## Before you call either\n\n### Adobe Firefly API\n\n1. Call the REST async endpoints directly. `@adobe/firefly-apis` 2.0.1 targets the removed synchronous paths and has no Image 5 or upscale methods\n2. Cache the IMS token and refresh it before its 24 hours run out\n3. Poll `/v3/status/{jobId}`, back off on 429 using the retry-after header, and download results within the hour their URLs stay valid\n4. Send `precise_upsampler_v1` to Upscale. `creative_upsampler_v1` returns 422 since 2026-04-24\n5. Image 5 lives at `/v4/images/generate-async`. Image 3 and 4 stay on `/v3/images/generate-async`\n\n### Iris-3B\n\n1. Check for an NVIDIA GPU with CUDA and Python 3.11 or newer before downloading. The base weights are about 12 GB, and Qwen3-VL-4B downloads on the first run\n2. Exclude `depth/*`, `upscaler/*` and `turbo/*` in `hf download` unless those models are needed. Each of the first two adds about 12 GB\n3. Don't pass `--steps`, `--cfg-scale`, `--negative-prompt`, `--order` or `--shift` with a Turbo checkpoint. The script exits with an error\n4. Pass `--seed` to reproduce an image, and set `--outdir`, since files are named after the prompt and a repeat run overwrites them\n5. Load only exported directories (`model.safetensors` and `config.yaml`). A training `.pth` is read with `torch.load(weights_only=False)`, so never load one from an untrusted source\n\n## Questions\n\n### Which is better for AI agents, Adobe Firefly API or Iris-3B?\n\nIris-3B scores 50.9 (D) on agent readiness against Adobe Firefly API's 49 (D), and leads in 2 of 7 scored categories. Adobe Firefly API leads on reliability, schema \u0026 documentation, security \u0026 auth and transparency \u0026 trust.\n\n### Do Adobe Firefly API and Iris-3B need an API key?\n\nAdobe Firefly API uses an OAuth sign-in. Iris-3B needs no key.\n\n### Can an agent call Adobe Firefly API and Iris-3B without installing anything?\n\nAdobe Firefly API has a hosted endpoint at https://firefly-api.adobe.io. No hosted endpoint is listed for Iris-3B.\n\n### Are Adobe Firefly API and Iris-3B open source?\n\nNo open-source release is listed for Adobe Firefly API. Iris-3B is open source (Apache-2.0 (code and weights)).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"adobe-firefly\", \"b\": \"iris-3b\"}`. From a terminal: `anchor compare adobe-firefly iris-3b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/adobe-firefly.json and https://www.anchorterminal.com/api/v1/tools/iris-3b.json\n\n## Other comparisons with Adobe Firefly API or Iris-3B\n\n- [Adobe Firefly API vs Black Forest Labs FLUX API](https://www.anchorterminal.com/compare/adobe-firefly-vs-black-forest-labs.md)\n- [Adobe Firefly API vs Bria API](https://www.anchorterminal.com/compare/adobe-firefly-vs-bria.md)\n- [Adobe Firefly API vs fal image models](https://www.anchorterminal.com/compare/adobe-firefly-vs-fal-image.md)\n- [Adobe Firefly API vs Google Imagen](https://www.anchorterminal.com/compare/adobe-firefly-vs-google-imagen.md)\n- [Adobe Firefly API vs Ideogram API](https://www.anchorterminal.com/compare/adobe-firefly-vs-ideogram.md)\n- [Adobe Firefly API vs Leonardo.Ai API](https://www.anchorterminal.com/compare/adobe-firefly-vs-leonardo-ai.md)\n- [Adobe Firefly API vs OpenAI Image API](https://www.anchorterminal.com/compare/adobe-firefly-vs-openai-image-api.md)\n- [Adobe Firefly API vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/adobe-firefly-vs-qwen-image-2-1.md)\n- [Adobe Firefly API vs Recraft API](https://www.anchorterminal.com/compare/adobe-firefly-vs-recraft.md)\n- [Adobe Firefly API vs Replicate image models](https://www.anchorterminal.com/compare/adobe-firefly-vs-replicate-image.md)\n- [Adobe Firefly API vs Seedream on BytePlus ModelArk](https://www.anchorterminal.com/compare/adobe-firefly-vs-seedream-on-byteplus-modelark.md)\n- [Adobe Firefly API vs Stability AI Image API](https://www.anchorterminal.com/compare/adobe-firefly-vs-stability-ai-image.md)\n- [Black Forest Labs FLUX API vs Iris-3B](https://www.anchorterminal.com/compare/black-forest-labs-vs-iris-3b.md)\n- [Bria API vs Iris-3B](https://www.anchorterminal.com/compare/bria-vs-iris-3b.md)\n- [fal image models vs Iris-3B](https://www.anchorterminal.com/compare/fal-image-vs-iris-3b.md)\n- [Google Imagen vs Iris-3B](https://www.anchorterminal.com/compare/google-imagen-vs-iris-3b.md)\n- [Ideogram API vs Iris-3B](https://www.anchorterminal.com/compare/ideogram-vs-iris-3b.md)\n- [Iris-3B vs Leonardo.Ai API](https://www.anchorterminal.com/compare/iris-3b-vs-leonardo-ai.md)\n- [Iris-3B vs OpenAI Image API](https://www.anchorterminal.com/compare/iris-3b-vs-openai-image-api.md)\n- [Iris-3B vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/iris-3b-vs-qwen-image-2-1.md)\n- [Iris-3B vs Recraft API](https://www.anchorterminal.com/compare/iris-3b-vs-recraft.md)\n- [Iris-3B vs Replicate image models](https://www.anchorterminal.com/compare/iris-3b-vs-replicate-image.md)\n- [Iris-3B vs Seedream on BytePlus ModelArk](https://www.anchorterminal.com/compare/iris-3b-vs-seedream-on-byteplus-modelark.md)\n- [Iris-3B vs Stability AI Image API](https://www.anchorterminal.com/compare/iris-3b-vs-stability-ai-image.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "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", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Adobe Firefly API vs Iris-3B", "url": "" } ], "description": "Iris-3B scores 50.9 (D) to Adobe Firefly's 49 (D) for image generation. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Adobe Firefly API D 49", "Iris-3B D 50.9", "scores" ], "h1": "Adobe Firefly API vs Iris-3B", "image": "https://www.anchorterminal.com/assets/og/compare-adobe-firefly-vs-iris-3b.png", "path": "/compare/adobe-firefly-vs-iris-3b", "published": "2026-10-01", "section": "tools", "title": "Adobe Firefly vs Iris-3B for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/adobe-firefly-vs-iris-3b" }, "tokens": { "markdown": 2550, "slim": 730 }, "version": 1 }