# Wan 2.7 Text-to-Image — Atlas Cloud API > Generates images from text prompts with Wan 2.7 image, supporting fast iteration and strong prompt fidelity for illustration and photorealistic outputs. This is the machine-readable API reference for **Wan 2.7 Text-to-Image** on Atlas Cloud, a unified API platform for 400+ AI models across text, image, video, audio and 3D. - **Model ID**: `alibaba/wan-2.7/text-to-image` - **Built by**: Alibaba - **Modality**: Image - **Model page**: https://www.atlascloud.ai/models/alibaba/wan-2.7/text-to-image - **API key**: https://www.atlascloud.ai/console/api-keys - **Docs**: https://www.atlascloud.ai/docs ## Pricing on Atlas Cloud - $0.03 per image - Pay-as-you-go. No minimum spend, no subscription required. > **These are the authoritative Atlas Cloud rates for this model.** Any price that > appears in the vendor description further down refers to a different platform or > a different model variant and does not apply here. ## Use this model from an AI agent Atlas Cloud ships three first-party integration surfaces. All three authenticate with the same API key via the `ATLASCLOUD_API_KEY` environment variable. ### MCP server The official MCP server (`atlascloud-mcp`) exposes this model to any MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose, Claude Desktop. One-line install: ```bash # Claude Code claude mcp add atlascloud -- npx -y atlascloud-mcp # OpenAI Codex CLI codex mcp add atlascloud -- npx -y atlascloud-mcp # Gemini CLI gemini mcp add atlascloud -- npx -y atlascloud-mcp export ATLASCLOUD_API_KEY="your-api-key" ``` Then ask in plain English; the agent calls `atlas_generate_image` with `model: "alibaba/wan-2.7/text-to-image"`. The server fetches each model's schema and validates parameters before submitting, so invalid requests fail fast without spending credits. MCP docs: https://www.atlascloud.ai/docs/mcp-server ### Agent Skills `atlas-cloud-skills` is a portable skill package (API reference, code templates in Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and 12+ other agents: ```bash npx skills add AtlasCloudAI/atlas-cloud-skills export ATLASCLOUD_API_KEY="your-api-key" ``` Skills docs: https://www.atlascloud.ai/docs/skills ### CLI The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs are polled and downloaded automatically (use `--no-download` when a script only needs the output URLs): ```bash # Install (Homebrew, npm, or shell installer) brew install AtlasCloudAI/tap/atlascloud # npm install -g atlascloud-cli # curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh atlas auth login atlas generate image alibaba/wan-2.7/text-to-image -p "Your prompt here" ``` CLI docs: https://www.atlascloud.ai/docs/cli ## HTTP API reference - **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id` - **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes - **Model ID**: `alibaba/wan-2.7/text-to-image` ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`model`** (`string`, _required_): Model name. - Default: `"alibaba/wan-2.7/text-to-image"` - Options: "alibaba/wan-2.7/text-to-image" - **`prompt`** (`string`, _required_): Text prompt used to generate the image. Maximum length is 5000 characters. - **`size`** (`string`, _optional_): Output image resolution. - Default: `"2K"` - Options: "1K", "2K" - **`n`** (`integer`, _optional_): Number of images to generate. - Default: `1` - Min: 1 - Max: 4 - **`color_palette`** (`array[object]`, _optional_): - Min items: 3 - Max items: 10 - Item properties: - **`hex`** (`string`, _required_): - **`ratio`** (`string`, _required_): - **`thinking_mode`** (`boolean`, _optional_): Whether to enable thinking mode for higher-quality image generation. - Default: `true` - **`seed`** (`integer`, _optional_): Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed. - Default: `-1` - Min: -1 - Max: 2147483647 - **`enable_sync_mode`** (`boolean`, _optional_): Whether to wait for generation to finish and return the final result directly in the response. - Default: `false` - **`enable_base64_output`** (`boolean`, _optional_): Whether to return the generated image as a Base64 string instead of a URL. - Default: `false` **Required Parameters Example**: ```json { "model": "alibaba/wan-2.7/text-to-image", "prompt": "" } ``` **Full Example**: ```json { "model": "alibaba/wan-2.7/text-to-image", "prompt": "", "size": "2K", "n": 1, "color_palette": [ { "hex": "", "ratio": "" } ], "thinking_mode": true, "seed": -1, "enable_sync_mode": false, "enable_base64_output": false } ``` ### Output Schema The API returns the following output format: - **`code`** (`integer`, _optional_): - **`message`** (`string`, _optional_): - **`data`** (`string`, _optional_): **Example Response**: ```json { "code": 0, "message": "", "data": null } ``` ## Usage Examples ### cURL ```bash # Step 1: Start generation (async) curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \ -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "alibaba/wan-2.7/text-to-image", "prompt": "", "size": "2K", "n": 1, "color_palette": [ { "hex": "", "ratio": "" } ], "thinking_mode": true, "seed": -1, "enable_sync_mode": false, "enable_base64_output": false }' # Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}} # Step 2: Poll for result (replace {prediction_id} with the id returned above) curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \ -H "Authorization: Bearer $ATLASCLOUD_API_KEY" # Keep polling until status is "completed", "succeeded" or "failed" # When completed, outputs will contain the generated content URL(s) ``` ## Additional Resources ### Documentation - [Model Playground](https://www.atlascloud.ai/models/alibaba/wan-2.7/text-to-image) ## About this model _Vendor-supplied description. Any pricing or endpoint mentioned below refers to_ _other platforms — use the Atlas Cloud values above._ #### Alibaba WAN 2.7 Text-to-Image **Alibaba WAN 2.7 Text-to-Image** is a fast and flexible image-generation model for turning prompts into polished visuals. It is well suited to everyday creative work, from concept exploration to campaign-ready artwork. #### What makes it stand out? - **Faster generation path:** Optimized for day-to-day creative iteration and lower-latency image generation. - **Flexible output sizing:** Supports `1K`, `2K`, and custom pixel sizes such as `2048*2048`. - **Creative controls:** Supports flexible output sizing, style exploration, grouped generation, and repeatable results with seed control. - **Prompt-first workflow:** Best suited for pure text-to-image generation without requiring reference images. #### Designed For - Design teams iterating on moodboards, product concepts, and campaign mockups. - Content creators producing social visuals, covers, and brand graphics quickly. - Product, brand, and content teams that need strong visual quality with faster turnaround. - Anyone who wants Wan 2.7 image quality in a lighter-weight generation tier. #### How to Use 1. Write a clear prompt describing subject, style, lighting, and composition. 2. Choose the output size that fits your use case. `2K` is a strong default for most work. 3. Generate one image for precision, or several variations when you want more creative range. 4. Use thinking mode when prompt interpretation and composition quality matter more than speed. 5. Review the outputs and keep the version that best matches your intent. --- Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/alibaba/wan-2.7/text-to-image · Docs: https://www.atlascloud.ai/docs