# FLUX Image Generator - Text to Image, Bulk Prompts (`seemuapps/flux-image-generator`) Actor Generate images from text prompts in bulk with FLUX. Square, portrait, landscape, and wide formats, up to 4 images per prompt, with stable hosted output URLs ready to export. - **URL**: https://apify.com/seemuapps/flux-image-generator.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** AI, Developer tools - **Stats:** 3 total users, 2 monthly users, 90.9% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## FLUX Image Generator - Text to Image Turn text prompts into high quality images. Generate one image or hundreds in a single run, choose from fast FLUX models or premium Gemini and GPT image models, and get every image hosted on a stable URL you can drop straight into a sheet, CMS, or app. ### Models - **FLUX schnell** - fastest and lowest cost, great for bulk runs - **FLUX dev** - higher quality FLUX - **Gemini 2.5 Flash Image / Nano Banana** and **Gemini 3 Flash Image / Nano Banana 2** - **Gemini 3 Pro Image** - premium quality - **GPT-5 Image** and **GPT-5 Image mini** FLUX models are fast and cheap; the Gemini and GPT image models produce premium results at a higher cost per image. ### What you get - A generated image for every prompt - Square, portrait, landscape, wide, and tall aspect ratios - Up to 4 variations per prompt - A stable hosted image URL for each result, plus the prompt, model, provider, and dimensions in one clean row - Optional fixed seed for reproducible results on FLUX models ### Use cases - Blog, ad, and social media visuals at scale - Product and concept mockups from a list of ideas - Thumbnails and hero images for content pipelines - Bulk creative testing across many prompts at once ### How to use 1. Add one or more **Prompts**, one image idea per line 2. Pick a **Model**: FLUX schnell for fast and cheap, FLUX dev for higher quality 3. Choose an **Aspect ratio** and **Images per prompt** 4. Optionally set an **Output format** and a fixed **Seed** 5. Run the actor. Each image appears as a row in the **Dataset** tab, and the files live in the **Key-value store** ### Input example ```json { "prompts": [ "A golden retriever puppy in a field of sunflowers, soft morning light, photorealistic", "Minimal product shot of a matte black water bottle on a marble surface" ], "model": "flux-schnell", "aspectRatio": "1:1", "imagesPerPrompt": 1, "outputFormat": "jpeg" } ```` ### Output example ```json { "prompt": "A golden retriever puppy in a field of sunflowers, soft morning light, photorealistic", "model": "flux-schnell", "aspectRatio": "1:1", "width": 1024, "height": 1024, "imageIndex": 1, "imageUrl": "https://api.apify.com/v2/key-value-stores/STORE_ID/records/image_1_1.jpeg", "imageKey": "image_1_1.jpeg", "nsfw": false, "seed": null, "status": "success", "error": null } ``` ### Free tier You can try this actor for free, with limits: - Up to **3 images** per run, generated on the fast **FLUX schnell** model - **3 runs per day**, with a **30-minute cooldown** between runs Upgrade to a paid plan to use every model (including the premium Gemini and GPT image models), generate up to 4 images per prompt across 25 prompts, and run without daily limits or cooldowns. ### Notes - The `imageUrl` is a stable, public link to the file in this run's key-value store. Download it or reference it directly. - Each prompt is generated independently, so one bad prompt never stops the rest of the run. Failed prompts come back with `status` set to `error` and a short message. - Use a fixed `seed` when you want the same prompt to produce the same image across runs. # Actor input Schema ## `prompts` (type: `array`): One or more text prompts describing the images to generate. Each prompt produces its own image (or several, see Images per prompt). ## `model` (type: `string`): Which image model to use. FLUX models are fast and low cost. Gemini and GPT image models produce premium quality at a higher cost per image. ## `aspectRatio` (type: `string`): Shape of the generated images. ## `imagesPerPrompt` (type: `integer`): How many images to generate for each prompt (1 to 4). ## `outputFormat` (type: `string`): File format of the generated images. Applies to FLUX models; Gemini and GPT image models return their native format (usually PNG). ## `seed` (type: `integer`): Optional fixed seed for reproducible results. Supported by FLUX models only; ignored by Gemini and GPT image models. ## Actor input object example ```json { "prompts": [ "A golden retriever puppy sitting in a field of sunflowers, soft morning light, photorealistic" ], "model": "flux-schnell", "aspectRatio": "1:1", "imagesPerPrompt": 1, "outputFormat": "jpeg" } ``` # Actor output Schema ## `results` (type: `string`): One record per generated image. Fields: prompt, model, aspectRatio, width, height, imageIndex, imageUrl (stable hosted URL), imageKey, sourceUrl, nsfw, seed, status, error. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "prompts": [ "A golden retriever puppy sitting in a field of sunflowers, soft morning light, photorealistic" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/flux-image-generator").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "prompts": ["A golden retriever puppy sitting in a field of sunflowers, soft morning light, photorealistic"] } # Run the Actor and wait for it to finish run = client.actor("seemuapps/flux-image-generator").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "prompts": [ "A golden retriever puppy sitting in a field of sunflowers, soft morning light, photorealistic" ] }' | apify call seemuapps/flux-image-generator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/flux-image-generator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FLUX Image Generator - Text to Image, Bulk Prompts", "description": "Generate images from text prompts in bulk with FLUX. Square, portrait, landscape, and wide formats, up to 4 images per prompt, with stable hosted output URLs ready to export.", "version": "1.1", "x-build-id": "7uB9u9OfbuaQvo8gq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~flux-image-generator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-flux-image-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~flux-image-generator/runs": { "post": { "operationId": "runs-sync-seemuapps-flux-image-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~flux-image-generator/run-sync": { "post": { "operationId": "run-sync-seemuapps-flux-image-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "prompts" ], "properties": { "prompts": { "title": "Prompts", "type": "array", "description": "One or more text prompts describing the images to generate. Each prompt produces its own image (or several, see Images per prompt).", "items": { "type": "string" } }, "model": { "title": "Model", "enum": [ "flux-schnell", "flux-dev", "gemini-2.5-flash-image", "gemini-3-flash-image", "gemini-3-pro-image", "gpt-image", "gpt-image-mini" ], "type": "string", "description": "Which image model to use. FLUX models are fast and low cost. Gemini and GPT image models produce premium quality at a higher cost per image.", "default": "flux-schnell" }, "aspectRatio": { "title": "Aspect ratio", "enum": [ "1:1", "3:4", "4:3", "16:9", "9:16" ], "type": "string", "description": "Shape of the generated images.", "default": "1:1" }, "imagesPerPrompt": { "title": "Images per prompt", "minimum": 1, "maximum": 4, "type": "integer", "description": "How many images to generate for each prompt (1 to 4).", "default": 1 }, "outputFormat": { "title": "Output format", "enum": [ "jpeg", "png", "webp" ], "type": "string", "description": "File format of the generated images. Applies to FLUX models; Gemini and GPT image models return their native format (usually PNG).", "default": "jpeg" }, "seed": { "title": "Seed (optional)", "minimum": 0, "type": "integer", "description": "Optional fixed seed for reproducible results. Supported by FLUX models only; ignored by Gemini and GPT image models." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```