Wan 2.7 Pro
Alibaba's high-fidelity image generation model with native 4K output, superior text rendering, and structured reasoning for complex scenes.
Overview
What is Wan 2.7 Pro
Wan 2.7 Pro is Alibaba's professional-grade text-to-image and image-editing model, released in April 2026. It delivers native 4K resolution, enhanced detail, and stronger semantic understanding for complex compositions. It features a 'thinking mode' that plans layout before rendering and excels at rendering legible in-image text and structured scenes.
Running it privately on Venice
On Venice, Wan 2.7 Pro runs under an anonymized privacy tier—your prompts are never stored, profiled, or used for training. This means you get enterprise-grade image generation with full privacy, ideal for sensitive or commercial creative workflows. The model’s zero retention policy ensures your intellectual property stays yours.
Assessment
Strengths and limitations
- Native 4K resolution output: genuine high-resolution detail without upscaling, ideal for print and large-format work.
- Superior in-image text rendering: handles dense text, formulas, and tables with high legibility.
- Thinking mode improves composition planning, resulting in better spatial coherence and prompt adherence in complex scenes.
- Strong semantic understanding and structural consistency across multi-element prompts.
- High-fidelity textures and lighting, suitable for photorealistic and production-grade visuals.
- Proprietary model: no open weights, so self-hosting or fine-tuning is not possible.
- Higher cost per image compared to standard-tier models, making it less ideal for rapid ideation.
- No support for video generation in this variant: Wan 2.7 Pro is image-only.
Samples
Sample outputs
Generated on Venice with our standard prompt suite — the same prompts we run through every model of this type, so you can judge it like-for-like.
A retro travel poster with the bold headline "VENICE" in large condensed serif type, sunset color palette, clean layout
Photorealistic close-up portrait of a weathered fisherman at golden hour, 85mm lens, shallow depth of field, natural skin texture
A small red cube balanced on top of a large glossy blue sphere, with a green cone to the right, plain light-grey studio background
Cozy watercolor illustration of a hillside village in autumn, warm tones, soft paper texture
Capabilities
What it supports
- Text to image
- Image to image
Specifications
Datasheet
- Maker
- Alibaba
- Released
- April 1, 2026
- Modality
- Text-to-image, image editing
- Max resolution
- 4096×4096 (4K native)
- Thinking mode
- Enabled by default
- Open weights
- No — proprietary
- Aspect ratios
- 1:1, 3:2, 16:9, 21:9, 9:16, 2:3, 3:4, 4:5
- Prompt limit
- 3,000 chars
- Privacy on Venice
- Anonymized — prompts not stored
- Available on Venice since
- Apr 2026
- License
- Proprietary
API
Call it from your code
Venice exposes this model through the REST API. Queue a generation with the model id.
curl https://api.venice.ai/api/v1/image/generate \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "wan-2-7-pro-text-to-image",
"prompt": "A serene mountain lake at dawn, photorealistic"
}' --output image.pngPricing
What it costs on Venice
Flat per-image pricing on Venice: $0.09 per generation.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Max resolution | Strongest at | Open weights | Price (Venice) |
|---|---|---|---|---|
| Wan 2.7 Pro | 4K | High-res print & text | No | $0.09 / image |
| Flux 2 Max | 4MP | Photoreal detail | No | $0.09 / image |
| Grok Imagine High Quality (SOTA) | — | Speed & integration | No | from $0.06 / image |
| Luma Uni-1 Max | — | 3D consistency | No | $0.12 / image |
Professional-tier model with native 4K and superior text rendering.
Use cases
What it is good for
- 01High-end print and magazine cover design requiring native 4K resolution.
- 02Marketing assets with embedded headlines, labels, or multilingual text.
- 03Technical illustrations, infographics, and diagrams with complex layouts.
- 04Creative workflows needing precise spatial and compositional control.
- 05Commercial projects where privacy and IP sovereignty are critical.
Prompting
Getting better results
Use explicit spatial descriptions (e.g., 'on the left,' 'above the building') to leverage thinking mode.
For text-heavy images, enclose the desired text in quotes to improve rendering accuracy.
Use seed values for reproducible outputs during final production stages.
Start with simpler prompts to test composition, then scale complexity.
Version history
Standard tier — lower fidelity, faster, cheaper.
Professional tier — higher fidelity, 4K native, better text.
FAQ
Frequently asked questions
Wan 2.7 Pro is Alibaba's high-fidelity text-to-image and image-editing model, released in April 2026. It supports native 4K output, advanced composition planning via thinking mode, and superior rendering of in-image text and complex scenes.
On Venice, Wan 2.7 Pro costs $0.09 per image generation. Upscaling options are available: $0.02 for 2× and $0.08 for 4× upscale.
No. Wan 2.7 Pro is a proprietary model developed by Alibaba. It is not open source, so it cannot be self-hosted or fine-tuned. Access is provided via API with per-image pricing.
No, Wan 2.7 Pro is a text-to-image and image-editing model only. It does not support tool use, web search, or reasoning beyond its built-in thinking mode for composition planning.
Wan 2.7 Pro natively supports 4096×4096 (4K) resolution across multiple aspect ratios including 1:1, 16:9, 9:16, and others. Output is genuine 4K, not upscaled.
Yes. Wan 2.7 Pro excels at rendering legible in-image text, including dense layouts, formulas, and tables, making it ideal for infographics and technical visuals.
Wan 2.7 Pro leads in native 4K output and text rendering, while Flux 2 Max offers strong photorealism and has open-weight variants. For print and text-heavy work, Wan 2.7 Pro is superior; for pure image quality, Flux 2 Max is competitive.
Run Wan 2.7 Pro privately
No prompt logging. No data used for training.