{
  "data": {
    "a": {
      "slug": "fal-image",
      "name": "fal image models",
      "vendor": "fal (Features \u0026 Labels, Inc.)",
      "vendorUrl": "https://fal.ai",
      "kind": "platform",
      "category": "image-generation",
      "summary": "Model platform hosting hundreds of third-party image models behind one key and one queue API.",
      "url": "https://www.anchorterminal.com/tools/fal-image",
      "markdownUrl": "https://www.anchorterminal.com/tools/fal-image.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/fal-image.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/fal-image.json",
      "repo": "https://github.com/fal-ai/fal-js",
      "license": "MIT",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://queue.fal.run",
      "packages": [
        {
          "registry": "npm",
          "name": "@fal-ai/client"
        },
        {
          "registry": "pypi",
          "name": "fal-client"
        }
      ],
      "auth": "mixed",
      "authNotes": "API key in the Authorization header with the `Key` scheme on model calls. The hosted MCP at https://mcp.fal.ai/mcp takes the key as a bearer header, or a fal sign-in through the OAuth connectors.",
      "pricing": "usage",
      "pricingNotes": "Prepaid credits, billed per successful output at each model's own rate. No charge for server errors, queue time or cold starts. Purchased credits expire after 365 days. FLUX.1 schnell $0.003 and FLUX.1 dev $0.025 per megapixel, FLUX.2 pro $0.03 for the first megapixel, Nano Banana 2 $0.08 and Nano Banana Pro $0.15 an image, Seedream 4.5 and Recraft V3 $0.04, Ideogram 3.0 $0.03 to $0.09 by quality (https://fal.ai/pricing).",
      "priceSummary": "Pay per use",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402 in the docs index or pricing docs (checked 2026-09-30).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 186,
        "npmWeekly": 1675192,
        "pypiWeekly": 824976,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://fal.ai/docs",
      "llmsTxt": "https://fal.ai/docs/llms.txt",
      "openapi": "https://api.fal.ai/v1/openapi.json",
      "capabilities": [
        "image.generate",
        "image.edit",
        "image.upscale",
        "image.vector",
        "image.reference"
      ],
      "tags": [
        "hosted",
        "model-platform",
        "mcp",
        "llms-txt",
        "openapi",
        "python",
        "typescript",
        "async-jobs",
        "webhooks",
        "open-weights"
      ],
      "lastRelease": "2026-09-21",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 65.2,
        "grade": "B",
        "agentReady": false,
        "rank": 329,
        "ranked": true,
        "rankOf": 961,
        "categoryRank": 2,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 72,
          "maintenance": 79,
          "payments": 20,
          "reliability": 73,
          "schema": 85,
          "security": 65,
          "transparency": 49
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Hundreds of image models, including FLUX, Nano Banana, GPT Image, Seedream, Recraft and Ideogram, on one key. Billing units vary by model, per image, per megapixel or per token.",
        "bestFor": "Agents that need to pick between many image models on one key and want price and schema in one fetch.",
        "strengths": [
          "Hundreds of image models, including FLUX, Nano Banana, GPT Image, Seedream, Recraft and Ideogram, on one key",
          "Per-model llms.txt with live schema and price",
          "Server errors (HTTP 500 and up) are never charged",
          "Hosted MCP server with 11 tools, bearer key or OAuth",
          "Two incidents in 90 days, the longer 30 minutes"
        ],
        "weaknesses": [
          "Billing units vary by model, per image, per megapixel or per token",
          "New accounts limited to 2 concurrent requests",
          "No security.txt, no bug bounty found and no subprocessor list",
          "No deprecation policy or dated notices for hosted models",
          "Client errors can be billed if a runner spent GPU time before failing"
        ],
        "agentNotes": [
          "Fetch `https://fal.ai/models/\u003cendpoint-id\u003e/llms.txt` before calling a model to get its schema and price",
          "POST to `https://queue.fal.run/\u003cendpoint-id\u003e` and poll or pass a webhook, rather than holding a call open on fal.run",
          "Use an API-scoped key for agents. ADMIN keys can deploy and manage apps",
          "Download outputs you need to keep. CDN retention defaults to at least 7 days, set `X-Fal-Object-Lifecycle-Preference` to change it",
          "Validate inputs before submitting, a malformed request can still be billed"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 4,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 65.2
          }
        ],
        "editorialScores": {
          "ergonomics": 72,
          "maintenance": 79,
          "payments": 20,
          "reliability": 73,
          "schema": 85,
          "security": 65,
          "transparency": 32
        },
        "provenanceScore": 66
      },
      "connect": {
        "http": "curl -X POST https://queue.fal.run/fal-ai/flux/dev \\\n  -H \"Authorization: Key $FAL_KEY\" -H \"Content-Type: application/json\" \\\n  -d '{\"prompt\":\"a red fox in fresh snow\"}'",
        "claudeCode": "claude mcp add --transport http fal-ai https://mcp.fal.ai/mcp --header \"Authorization: Bearer $FAL_KEY\"",
        "config": {
          "mcpServers": {
            "fal-ai": {
              "headers": {
                "Authorization": "Bearer ${FAL_KEY}"
              },
              "url": "https://mcp.fal.ai/mcp"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/image.generate",
        "tool": "https://letme.dev/fal-image"
      },
      "sameCompany": [
        "fal-video",
        "fal-music"
      ],
      "area": "content",
      "unitPrices": [
        {
          "item": "FLUX.1 dev",
          "unit": "image",
          "usd": 0.025,
          "note": "1024x1024 (1 MP), billed per megapixel"
        },
        {
          "item": "FLUX.1 schnell",
          "unit": "image",
          "usd": 0.003,
          "note": "1024x1024 (1 MP), billed per megapixel"
        },
        {
          "item": "FLUX.2 pro",
          "unit": "image",
          "usd": 0.03,
          "note": "1024x1024. $0.015 per extra megapixel"
        },
        {
          "item": "Nano Banana 2",
          "unit": "image",
          "usd": 0.08,
          "note": "1K output. 1.5x at 2K, 2x at 4K"
        },
        {
          "item": "Nano Banana Pro",
          "unit": "image",
          "usd": 0.15,
          "note": "standard resolution. 2x at 4K"
        },
        {
          "item": "Seedream 4.5",
          "unit": "image",
          "usd": 0.04
        },
        {
          "item": "Recraft V3",
          "unit": "image",
          "usd": 0.04,
          "note": "$0.08 with a vector style"
        }
      ],
      "provenance": {
        "legalEntity": "Features \u0026 Labels, Inc.",
        "domain": "fal.ai",
        "domainRegistered": "2020-11-13",
        "endpointOnVendorDomain": false,
        "terms": "https://fal.ai/legal/terms-of-service",
        "privacy": "https://fal.ai/legal/privacy-policy",
        "statusPage": "https://status.fal.ai",
        "changelog": "https://fal.ai/docs/changelog",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "Inference runs on queue.fal.run and fal.run, a separate domain from fal.ai",
          "remoteUrl is the queue base. A bare GET there returns 404. Model calls go to /\u003cendpoint-id\u003e"
        ],
        "score": 66
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/fal-image.json",
      "live": {
        "slug": "fal-image",
        "probe": {
          "target": "https://queue.fal.run",
          "method": "get",
          "lastAt": "2026-10-11T02:46:25.035743687Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 1244,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 318,
          "p95ms24h": 362,
          "samples24h": 248,
          "samples30d": 2712,
          "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": 29,
              "ok": 29
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.fal.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-11T01:36:32.432694204Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "fal-ai/fal-js",
            "version": "client-v1.10.1",
            "released": "2026-05-04",
            "seenAt": "2026-10-10T17:46:35.762061594Z"
          },
          {
            "registry": "npm",
            "name": "@fal-ai/client",
            "version": "1.10.1",
            "seenAt": "2026-10-10T17:46:34.707419788Z"
          },
          {
            "registry": "pypi",
            "name": "fal-client",
            "version": "1.0.3",
            "released": "2026-09-21",
            "seenAt": "2026-10-10T17:46:35.57460397Z"
          }
        ],
        "githubStars": 187,
        "npmWeekly": 1723470,
        "pypiWeekly": 729757,
        "securityTxt": {
          "url": "https://fal.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-10T15:40:38.518685333Z"
        },
        "llmsTxt": {
          "url": "https://fal.ai/docs/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-10T14:04:12.538956086Z"
        },
        "domain": {
          "domain": "fal.ai",
          "registered": "2020-11-13",
          "source": "https://rdap.identitydigital.services/rdap/domain/fal.ai",
          "checkedAt": "2026-10-04T13:04:33.919358701Z"
        },
        "pages": [
          {
            "url": "https://fal.ai/docs/changelog",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-10T19:03:35.229466613Z",
            "changedAt": "2026-10-10T19:03:35.229466613Z",
            "fingerprint": "63b0d7c3b211"
          },
          {
            "url": "https://fal.ai/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-10T19:03:43.884538997Z",
            "changedAt": "2026-10-08T18:20:21.57604428Z",
            "fingerprint": "1234f2aa3e34"
          },
          {
            "url": "https://fal.ai/legal/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-10T19:03:39.446580515Z",
            "changedAt": "2026-10-07T18:06:08.126413382Z",
            "fingerprint": "1a7f6821e9f2"
          },
          {
            "url": "https://fal.ai/legal/terms-of-service",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-10T19:03:41.795048945Z",
            "changedAt": "2026-10-07T18:06:10.325846357Z",
            "fingerprint": "b564469d1d9a"
          }
        ],
        "updatedAt": "2026-10-11T02:46:25.035743687Z"
      }
    },
    "answer": "fal image models and Qwen-Image 2.1 (Model Studio) score within a point of each other on agent readiness, 65.2 (B) and 64.7 (B). Qwen-Image 2.1 (Model Studio) leads on security \u0026 auth and transparency \u0026 trust.",
    "b": {
      "slug": "qwen-image-2-1",
      "name": "Qwen-Image 2.1 (Model Studio)",
      "vendor": "Alibaba Cloud",
      "vendorUrl": "https://www.alibabacloud.com",
      "kind": "model",
      "category": "image-generation",
      "summary": "Qwen-Image 2.1 is Alibaba's image model for text-to-image and image editing with up to 10 reference images and transparent output, callable as qwen-image-2.1-pro through Alibaba Cloud Model Studio's DashScope and OpenAI-compatible APIs.",
      "url": "https://www.anchorterminal.com/tools/qwen-image-2-1",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen-image-2-1.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen-image-2-1.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen-image-2-1.json",
      "repo": "https://huggingface.co/Qwen/Qwen-Image-2.1",
      "license": "Closed API under Alibaba Cloud's product terms. Qwen-Image-2.1 weights are on Hugging Face under the Qwen Research License, for non-commercial use only.",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://dashscope-intl.aliyuncs.com/api/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "dashscope"
        }
      ],
      "auth": "api-key",
      "authNotes": "Bearer Model Studio API key, created per region in the console by an account or RAM user with API-Key permission. Keys can be limited to chosen models and an IP allow-list of up to 20 entries, and reset. The model, endpoint and key must be in the same region. Async calls add `X-DashScope-Async: enable`.",
      "pricing": "usage",
      "pricingNotes": "qwen-image-2.1-pro is $0.04 an image in Singapore (International) and $0.035333 in Beijing, Virginia, Frankfurt, Tokyo and Hong Kong, list prices without promotions (model page, checked 10 October 2026). New Singapore users get a 90-day free quota, but whether it covers this model was not confirmed.",
      "priceSummary": "Pay per use",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the Model Studio llms.txt, the Qwen image API reference or the model page, checked 10 October 2026.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-10"
      },
      "docsUrl": "https://www.alibabacloud.com/help/en/model-studio/qwen-image-generation-and-editing-api-reference",
      "llmsTxt": "https://docs.modelstudio.console.alibabacloud.com/llms.txt",
      "capabilities": [
        "image.generate",
        "image.edit",
        "image.reference"
      ],
      "tags": [
        "official",
        "hosted",
        "usage-priced",
        "open-weights",
        "llms-txt",
        "openai-compatible",
        "async-jobs",
        "python",
        "sla",
        "soc2"
      ],
      "lastRelease": "2026-10-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.7,
        "grade": "B",
        "agentReady": false,
        "rank": 347,
        "ranked": true,
        "rankOf": 961,
        "categoryRank": 3,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 73,
          "maintenance": 77,
          "payments": 20,
          "reliability": 70,
          "schema": 66,
          "security": 75,
          "transparency": 66
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-10"
        },
        "negative": 0,
        "verdict": "qwen-image-2.1-pro generates and edits images with up to 10 references and transparent output, at $0.04 an image in Singapore, through an OpenAI-compatible endpoint or DashScope. Model Studio publishes a 99.9 per cent SLA and a no-training statement. The model allows 20 requests a minute, has no OpenAPI file, and its open weights are for non-commercial use only.",
        "bestFor": "Low-cost image generation and multi-reference editing with transparent PNG output, for agents already on Model Studio or using the OpenAI Images protocol.",
        "strengths": [
          "Text-to-image and editing in one model, with 1 to 10 reference images and transparent output decided from the prompt",
          "$0.04 an image in Singapore and $0.035333 in five other regions, published without a login",
          "OpenAI-compatible /images/generations endpoint beside DashScope sync and async calls",
          "Keys can be limited to chosen models and an IP allow-list, and the audit log records each call",
          "The Model Studio privacy notice says customer data is never used for training"
        ],
        "weaknesses": [
          "20 requests a minute in every region",
          "No OpenAPI or other machine-readable contract for the image endpoints",
          "Result URLs expire after 24 hours, and the OpenAI-compatible mode ignores `b64_json`",
          "`negative_prompt` works only on the qwen-image-3.0 series, not on qwen-image-2.1-pro",
          "Qwen-Image-2.1 weights are under a non-commercial research licence, so self-hosting is not an option for commercial work"
        ],
        "agentNotes": [
          "Use the same region for the key, the model and the endpoint. Cross-region calls fail",
          "Download each result within 24 hours. The URL expires and the image is purged",
          "With the OpenAI SDK, pass `image`, `seed`, `prompt_extend` and `watermark` through `extra_body`, and write size as `1024x1024`, not `1024*1024`",
          "Set a client timeout of up to 600 seconds for several outputs, or use the async DashScope call and poll the task id",
          "Do not send `prompt_extend_mode: agent` with input images. It returns 400"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.7
          }
        ],
        "editorialScores": {
          "ergonomics": 73,
          "maintenance": 77,
          "payments": 20,
          "reliability": 70,
          "schema": 66,
          "security": 75,
          "transparency": 60
        },
        "provenanceScore": 72
      },
      "connect": {
        "install": "pip install dashscope",
        "http": "curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/images/generations' \\\n  --header 'Content-Type: application/json' \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n  --data '{\"model\":\"qwen-image-2.1-pro\",\"prompt\":\"A paper boat sticker on a transparent background\",\"n\":1}'"
      },
      "letme": {
        "capability": "https://letme.dev/image.generate",
        "tool": "https://letme.dev/qwen-image-2-1"
      },
      "sameCompany": [
        "alibaba-wan"
      ],
      "area": "content",
      "unitPrices": [
        {
          "item": "qwen-image-2.1-pro, Singapore",
          "unit": "image",
          "usd": 0.04,
          "note": "International scope, list price"
        },
        {
          "item": "qwen-image-2.1-pro, Beijing, Virginia, Frankfurt, Tokyo, Hong Kong",
          "unit": "image",
          "usd": 0.035333,
          "note": "list price"
        }
      ],
      "provenance": {
        "legalEntity": "Alibaba Cloud (Singapore) Private Limited",
        "domain": "alibabacloud.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://www.alibabacloud.com/help/en/legal/latest/alibaba-cloud-international-website-product-terms-of-service-v-3-8-0",
        "privacy": "https://www.alibabacloud.com/help/en/model-studio/privacy-notice",
        "statusPage": "https://status.alibabacloud.com",
        "changelog": "https://www.alibabacloud.com/help/en/model-studio/newly-released-models",
        "securityTxt": "none",
        "checked": "2026-10-10",
        "notes": [
          "The endpoints are on aliyuncs.com, Alibaba Cloud's service domain (dashscope-intl.aliyuncs.com and per-workspace maas.aliyuncs.com hosts), as in the alibaba-wan listing.",
          "www.alibabacloud.com/.well-known/security.txt returns an HTML not-found page.",
          "status.alibabacloud.com renders in the browser only and its incident history was not read.",
          "The legal entity and terms URL follow the alibaba-wan listing and were not re-read on 10 October."
        ],
        "score": 72
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen-image-2-1.json",
      "live": {
        "slug": "qwen-image-2-1",
        "probe": {
          "target": "https://dashscope-intl.aliyuncs.com/api/v1",
          "method": "get",
          "lastAt": "2026-10-11T02:46:38.126307135Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 232,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 170,
          "p95ms24h": 246,
          "samples24h": 30,
          "samples30d": 30,
          "days": [
            {
              "date": "2026-10-10",
              "probes": 1,
              "ok": 1
            },
            {
              "date": "2026-10-11",
              "probes": 29,
              "ok": 29
            }
          ]
        },
        "updatedAt": "2026-10-11T02:46:38.126307135Z"
      }
    },
    "facts": [
      {
        "a": "Platform",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "fal (Features \u0026 Labels, Inc.)",
        "b": "Alibaba Cloud",
        "name": "Vendor"
      },
      {
        "a": "https://queue.fal.run",
        "b": "https://dashscope-intl.aliyuncs.com/api/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, Streamable HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "MIT",
        "b": "Closed API under Alibaba Cloud's product terms. Qwen-Image-2.1 weights are on Hugging Face under the Qwen Research License, for non-commercial use only.",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-21",
        "b": "2026-10-02",
        "name": "Last release"
      },
      {
        "a": "2026-09-08",
        "b": "couldn't be read",
        "name": "Terms last updated"
      },
      {
        "a": "2026-07-22",
        "b": "",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "couldn't be read",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "couldn't be read",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "yes",
        "b": "couldn't be read",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "186 stars, 1.7M npm/wk, 825k PyPI/wk",
        "b": "none",
        "name": "Popularity"
      },
      {
        "a": "4/5 (2)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "fal image models and Qwen-Image 2.1 (Model Studio) score within a point of each other on agent readiness, 65.2 (B) and 64.7 (B). Qwen-Image 2.1 (Model Studio) leads on security \u0026 auth and transparency \u0026 trust.",
        "question": "Which is better for AI agents, fal image models or Qwen-Image 2.1 (Model Studio)?"
      },
      {
        "answer": "Yes. fal image models has a hosted endpoint at https://queue.fal.run and Qwen-Image 2.1 (Model Studio) at https://dashscope-intl.aliyuncs.com/api/v1.",
        "question": "Can an agent call fal image models and Qwen-Image 2.1 (Model Studio) without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 85 against 66"
        ],
        "also": null,
        "goodFor": "Agents that need to pick between many image models on one key and want price and schema in one fetch.",
        "slug": "fal-image",
        "watchFor": "Billing units vary by model, per image, per megapixel or per token"
      },
      {
        "aheadOn": [
          "Security \u0026 auth, 75 against 65",
          "Transparency \u0026 trust, 66 against 49"
        ],
        "also": null,
        "goodFor": "Low-cost image generation and multi-reference editing with transparent PNG output, for agents already on Model Studio or using the OpenAI Images protocol.",
        "slug": "qwen-image-2-1",
        "watchFor": "20 requests a minute in every region"
      }
    ],
    "job": {
      "capability": "image.generate",
      "name": "Image generation"
    },
    "others": [
      {
        "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-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/black-forest-labs-vs-fal-image.json",
        "title": "Black Forest Labs FLUX API vs fal image models",
        "url": "https://www.anchorterminal.com/compare/black-forest-labs-vs-fal-image"
      },
      {
        "json": "https://www.anchorterminal.com/compare/black-forest-labs-vs-qwen-image-2-1.json",
        "title": "Black Forest Labs FLUX API vs Qwen-Image 2.1 (Model Studio)",
        "url": "https://www.anchorterminal.com/compare/black-forest-labs-vs-qwen-image-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bria-vs-fal-image.json",
        "title": "Bria API vs fal image models",
        "url": "https://www.anchorterminal.com/compare/bria-vs-fal-image"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bria-vs-qwen-image-2-1.json",
        "title": "Bria API vs Qwen-Image 2.1 (Model Studio)",
        "url": "https://www.anchorterminal.com/compare/bria-vs-qwen-image-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-google-imagen.json",
        "title": "fal image models vs Google Imagen",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-google-imagen"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-ideogram.json",
        "title": "fal image models vs Ideogram API",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-ideogram"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-leonardo-ai.json",
        "title": "fal image models vs Leonardo.Ai API",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-leonardo-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-openai-image-api.json",
        "title": "fal image models vs OpenAI Image API",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-openai-image-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-recraft.json",
        "title": "fal image models vs Recraft API",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-recraft"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-replicate-image.json",
        "title": "fal image models vs Replicate image models",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-replicate-image"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-seedream-on-byteplus-modelark.json",
        "title": "fal image models vs Seedream on BytePlus ModelArk",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-seedream-on-byteplus-modelark"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fal-image-vs-stability-ai-image.json",
        "title": "fal image models vs Stability AI Image API",
        "url": "https://www.anchorterminal.com/compare/fal-image-vs-stability-ai-image"
      },
      {
        "json": "https://www.anchorterminal.com/compare/google-imagen-vs-qwen-image-2-1.json",
        "title": "Google Imagen vs Qwen-Image 2.1 (Model Studio)",
        "url": "https://www.anchorterminal.com/compare/google-imagen-vs-qwen-image-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ideogram-vs-qwen-image-2-1.json",
        "title": "Ideogram API vs Qwen-Image 2.1 (Model Studio)",
        "url": "https://www.anchorterminal.com/compare/ideogram-vs-qwen-image-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/leonardo-ai-vs-qwen-image-2-1.json",
        "title": "Leonardo.Ai API vs Qwen-Image 2.1 (Model Studio)",
        "url": "https://www.anchorterminal.com/compare/leonardo-ai-vs-qwen-image-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openai-image-api-vs-qwen-image-2-1.json",
        "title": "OpenAI Image API vs Qwen-Image 2.1 (Model Studio)",
        "url": "https://www.anchorterminal.com/compare/openai-image-api-vs-qwen-image-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-recraft.json",
        "title": "Qwen-Image 2.1 (Model Studio) vs Recraft API",
        "url": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-recraft"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-replicate-image.json",
        "title": "Qwen-Image 2.1 (Model Studio) vs Replicate image models",
        "url": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-replicate-image"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-seedream-on-byteplus-modelark.json",
        "title": "Qwen-Image 2.1 (Model Studio) vs Seedream on BytePlus ModelArk",
        "url": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-seedream-on-byteplus-modelark"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-stability-ai-image.json",
        "title": "Qwen-Image 2.1 (Model Studio) vs Stability AI Image API",
        "url": "https://www.anchorterminal.com/compare/qwen-image-2-1-vs-stability-ai-image"
      }
    ],
    "scores": [
      {
        "by": 3,
        "edge": "fal-image",
        "fal-image": 73,
        "key": "reliability",
        "name": "Reliability",
        "qwen-image-2-1": 70,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 19,
        "edge": "fal-image",
        "fal-image": 85,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "qwen-image-2-1": 66,
        "weight": 13
      },
      {
        "by": 1,
        "edge": "qwen-image-2-1",
        "fal-image": 72,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "qwen-image-2-1": 73,
        "weight": 13
      },
      {
        "by": 10,
        "edge": "qwen-image-2-1",
        "fal-image": 65,
        "key": "security",
        "name": "Security \u0026 auth",
        "qwen-image-2-1": 75,
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "fal-image": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "qwen-image-2-1": 20,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 2,
        "edge": "fal-image",
        "fal-image": 79,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "qwen-image-2-1": 77,
        "weight": 7
      },
      {
        "by": 17,
        "edge": "qwen-image-2-1",
        "fal-image": 49,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "qwen-image-2-1": 66,
        "weight": 7
      }
    ],
    "summary": "fal image models and Qwen-Image 2.1 (Model Studio) score within a point of each other on agent readiness, 65.2 (B) and 64.7 (B). Qwen-Image 2.1 (Model Studio) leads on security \u0026 auth and transparency \u0026 trust. Both do image generation.",
    "verdicts": {
      "fal-image": "Hundreds of image models, including FLUX, Nano Banana, GPT Image, Seedream, Recraft and Ideogram, on one key. Billing units vary by model, per image, per megapixel or per token.",
      "qwen-image-2-1": "qwen-image-2.1-pro generates and edits images with up to 10 references and transparent output, at $0.04 an image in Singapore, through an OpenAI-compatible endpoint or DashScope. Model Studio publishes a 99.9 per cent SLA and a no-training statement. The model allows 20 requests a minute, has no OpenAPI file, and its open weights are for non-commercial use only."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/fal-image-vs-qwen-image-2-1",
    "json": "https://www.anchorterminal.com/compare/fal-image-vs-qwen-image-2-1.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/fal-image-vs-qwen-image-2-1.md",
    "slim": "https://www.anchorterminal.com/compare/fal-image-vs-qwen-image-2-1.min.md"
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  "markdown": "fal image models and Qwen-Image 2.1 (Model Studio) score within a point of each other on agent readiness, 65.2 (B) and 64.7 (B). Qwen-Image 2.1 (Model Studio) leads on security \u0026 auth and transparency \u0026 trust. Both do image generation.\n\n- fal image models: grade B, 65.2/100, rank #329 of 961. Markdown https://www.anchorterminal.com/tools/fal-image.md · JSON https://www.anchorterminal.com/api/v1/tools/fal-image.json\n- Qwen-Image 2.1 (Model Studio): grade B, 64.7/100, rank #347 of 961. Markdown https://www.anchorterminal.com/tools/qwen-image-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen-image-2-1.json\n- Best image generation for AI agents: https://www.anchorterminal.com/best/image-generation/index.md\n- All 78 image comparisons: https://www.anchorterminal.com/compare/image-generation/index.md\n\n## Which one, for what\n\n### fal image models (B)\n\nGood for: Agents that need to pick between many image models on one key and want price and schema in one fetch.\n\nAhead on:\n- Schema \u0026 documentation, 85 against 66\n\nWatch for: Billing units vary by model, per image, per megapixel or per token\n\n### Qwen-Image 2.1 (Model Studio) (B)\n\nGood for: Low-cost image generation and multi-reference editing with transparent PNG output, for agents already on Model Studio or using the OpenAI Images protocol.\n\nAhead on:\n- Security \u0026 auth, 75 against 65\n- Transparency \u0026 trust, 66 against 49\n\nWatch for: 20 requests a minute in every region\n\n\n## Score by category\n\n| Category | Weight | fal image models | Qwen-Image 2.1 (Model Studio) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 73 | 70 | fal image models +3 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 66 | fal image models +19 |\n| Agent ergonomics | 13% (16.2 this run) | 72 | 73 | Qwen-Image 2.1 (Model Studio) +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 65 | 75 | Qwen-Image 2.1 (Model Studio) +10 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 79 | 77 | fal image models +2 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 49 | 66 | Qwen-Image 2.1 (Model Studio) +17 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **65.2 · B** | **64.7 · B** | |\n\n## Facts side by side\n\n| Fact | fal image models | Qwen-Image 2.1 (Model Studio) |\n| --- | --- | --- |\n| Kind | Platform | Model API |\n| Vendor | fal (Features \u0026 Labels, Inc.) | Alibaba Cloud |\n| Hosted endpoint | `https://queue.fal.run` | `https://dashscope-intl.aliyuncs.com/api/v1` |\n| Transports | HTTP, Streamable HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | MIT | Closed API under Alibaba Cloud's product terms. Qwen-Image-2.1 weights are on Hugging Face under the Qwen Research License, for non-commercial use only. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-21 | 2026-10-02 |\n| Terms last updated | 2026-09-08 | couldn't be read |\n| Privacy policy last updated | 2026-07-22 |  |\n| Customer content may train models | not found in the text | couldn't be read |\n| Terms restrict automated access | yes | couldn't be read |\n| Terms restrict benchmarking | yes | couldn't be read |\n| Terms or service can change without notice | not found in the text | couldn't be read |\n| Arbitration or class-action waiver | yes | couldn't be read |\n| Popularity | 186 stars, 1.7M npm/wk, 825k PyPI/wk | none |\n| Agent reviews | 4/5 (2) | none |\n\n## Verdicts\n\n**fal image models.** Hundreds of image models, including FLUX, Nano Banana, GPT Image, Seedream, Recraft and Ideogram, on one key. Billing units vary by model, per image, per megapixel or per token.\n\n**Qwen-Image 2.1 (Model Studio).** qwen-image-2.1-pro generates and edits images with up to 10 references and transparent output, at $0.04 an image in Singapore, through an OpenAI-compatible endpoint or DashScope. Model Studio publishes a 99.9 per cent SLA and a no-training statement. The model allows 20 requests a minute, has no OpenAPI file, and its open weights are for non-commercial use only.\n\n## Before you call either\n\n### fal image models\n\n1. Fetch `https://fal.ai/models/\u003cendpoint-id\u003e/llms.txt` before calling a model to get its schema and price\n2. POST to `https://queue.fal.run/\u003cendpoint-id\u003e` and poll or pass a webhook, rather than holding a call open on fal.run\n3. Use an API-scoped key for agents. ADMIN keys can deploy and manage apps\n4. Download outputs you need to keep. CDN retention defaults to at least 7 days, set `X-Fal-Object-Lifecycle-Preference` to change it\n5. Validate inputs before submitting, a malformed request can still be billed\n\n### Qwen-Image 2.1 (Model Studio)\n\n1. Use the same region for the key, the model and the endpoint. Cross-region calls fail\n2. Download each result within 24 hours. The URL expires and the image is purged\n3. With the OpenAI SDK, pass `image`, `seed`, `prompt_extend` and `watermark` through `extra_body`, and write size as `1024x1024`, not `1024*1024`\n4. Set a client timeout of up to 600 seconds for several outputs, or use the async DashScope call and poll the task id\n5. Do not send `prompt_extend_mode: agent` with input images. It returns 400\n\n## Questions\n\n### Which is better for AI agents, fal image models or Qwen-Image 2.1 (Model Studio)?\n\nfal image models and Qwen-Image 2.1 (Model Studio) score within a point of each other on agent readiness, 65.2 (B) and 64.7 (B). Qwen-Image 2.1 (Model Studio) leads on security \u0026 auth and transparency \u0026 trust.\n\n### Can an agent call fal image models and Qwen-Image 2.1 (Model Studio) without installing anything?\n\nYes. fal image models has a hosted endpoint at https://queue.fal.run and Qwen-Image 2.1 (Model Studio) at https://dashscope-intl.aliyuncs.com/api/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/fal-image-vs-qwen-image-2-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/fal-image-vs-qwen-image-2-1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"fal-image\", \"b\": \"qwen-image-2-1\"}`. From a terminal: `anchor compare fal-image qwen-image-2-1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/fal-image.json and https://www.anchorterminal.com/api/v1/tools/qwen-image-2-1.json\n\n## Other comparisons with fal image models or Qwen-Image 2.1 (Model Studio)\n\n- [Adobe Firefly API vs fal image models](https://www.anchorterminal.com/compare/adobe-firefly-vs-fal-image.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- [Black Forest Labs FLUX API vs fal image models](https://www.anchorterminal.com/compare/black-forest-labs-vs-fal-image.md)\n- [Black Forest Labs FLUX API vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/black-forest-labs-vs-qwen-image-2-1.md)\n- [Bria API vs fal image models](https://www.anchorterminal.com/compare/bria-vs-fal-image.md)\n- [Bria API vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/bria-vs-qwen-image-2-1.md)\n- [fal image models vs Google Imagen](https://www.anchorterminal.com/compare/fal-image-vs-google-imagen.md)\n- [fal image models vs Ideogram API](https://www.anchorterminal.com/compare/fal-image-vs-ideogram.md)\n- [fal image models vs Leonardo.Ai API](https://www.anchorterminal.com/compare/fal-image-vs-leonardo-ai.md)\n- [fal image models vs OpenAI Image API](https://www.anchorterminal.com/compare/fal-image-vs-openai-image-api.md)\n- [fal image models vs Recraft API](https://www.anchorterminal.com/compare/fal-image-vs-recraft.md)\n- [fal image models vs Replicate image models](https://www.anchorterminal.com/compare/fal-image-vs-replicate-image.md)\n- [fal image models vs Seedream on BytePlus ModelArk](https://www.anchorterminal.com/compare/fal-image-vs-seedream-on-byteplus-modelark.md)\n- [fal image models vs Stability AI Image API](https://www.anchorterminal.com/compare/fal-image-vs-stability-ai-image.md)\n- [Google Imagen vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/google-imagen-vs-qwen-image-2-1.md)\n- [Ideogram API vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/ideogram-vs-qwen-image-2-1.md)\n- [Leonardo.Ai API vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/leonardo-ai-vs-qwen-image-2-1.md)\n- [OpenAI Image API vs Qwen-Image 2.1 (Model Studio)](https://www.anchorterminal.com/compare/openai-image-api-vs-qwen-image-2-1.md)\n- [Qwen-Image 2.1 (Model Studio) vs Recraft API](https://www.anchorterminal.com/compare/qwen-image-2-1-vs-recraft.md)\n- [Qwen-Image 2.1 (Model Studio) vs Replicate image models](https://www.anchorterminal.com/compare/qwen-image-2-1-vs-replicate-image.md)\n- [Qwen-Image 2.1 (Model Studio) vs Seedream on BytePlus ModelArk](https://www.anchorterminal.com/compare/qwen-image-2-1-vs-seedream-on-byteplus-modelark.md)\n- [Qwen-Image 2.1 (Model Studio) vs Stability AI Image API](https://www.anchorterminal.com/compare/qwen-image-2-1-vs-stability-ai-image.md)\n",
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      {
        "name": "fal image models vs Qwen-Image 2.1 (Model Studio)",
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    "published": "2026-10-01",
    "section": "tools",
    "title": "fal image models vs Qwen-Image 2.1 for AI agents (2026)",
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}