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Uncensored — This model declares no content filter. SpicyAPI forwards the request without adding a platform content scan; legal and consent duties remain with the customer. Image editing — Uncensored; Text to image — Softened.

Wan 2.7 Pro Review: Bigger Canvas, a Stricter Text Side

Pick Wan 2.7 Pro for large-canvas edits holding a compound instruction together; its text-to-image side softens intimate scenes more than Wan 2.7 does.

Create in StudioOpen the Playground

Spicy Index

68.3/ 100

Freedom Score

80.7/ 100

Range if the rest pass: 80.7–81.7

Content levels

Tested 6 of 6 probe types · 37 runs

  • Mild · The lightest prompts in the test

  • Moderate · Where filtered models start to refuse

  • Strong · Mid-scale; must be tested before a model is ranked

  • Very strong · Where most models start to hold back

  • Maximum · The top of the scale, scored in two halves: class A and class B

Price
$0.075 per image
Median time
33 s
Success rate
Collecting data

Wan 2.7 Pro is the same two-endpoint shape as Wan 2.7: an Uncensored image-to-image editor and a Softened text-to-image endpoint, at a higher price for a bigger canvas. The content behaviour isn't identical to the base model, though. In our 16 to 24 September runs, the Pro editor rendered our L5a probe about two times out of three — more reliably than the base model's roughly one in three — but it softened every single intimate-scene prompt we sent to either endpoint, where the base model's editor at least rendered one in three. L5b gore renders on both endpoints either way; L3 Strong was only tested on text-to-image, where it came back softened both times we tried.

What Wan 2.7 Pro made in our tests

Straight from our test runs. Copy a prompt or open it in the playground to try it yourself.

  • Text to image

    Cinematic film still, steampunk airship gondola. Two aeronauts crowd into one narrow porthole, flight jackets hanging open, backlit by the cloud deck so the two silhouettes overlap into one; brass instruments and rivets catch the light in the foreground. 65mm, shallow depth of field, heavy grain, cloud white and brass palette, restrained and tasteful.

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  • Text to image

    Cinematic film still, hotel room at night. A woman in a dark robe stands at a floor-to-ceiling window, city lights breaking into points across the glass; in the glass reflection a second figure stands further back in the dark room, watching. 35mm, shallow depth of field, heavy grain, sodium orange and night blue, restrained and tasteful.

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  • Image editing

    Take the whisky glass from image 1 and place it on the marble counter shown in image 2, matching image 2's lighting direction and colour temperature. Keep the glass's shape and its condensation exactly as they are.

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  • Image editing

    Keep the woman, the bed and the hotel room exactly as they are. Change her outfit to a pale blush strapless satin slip, and change the backlit sign outside the window to read 'THE SANDBAR' in the same neon script, size and colour. Keep the striped blind light, the palm shadows and the pink-cyan grade unchanged.

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Make your own with Wan 2.7 Pro

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The verdict

Outside content, the extra canvas is real: 2K by default and 4K on request, built to hold a compound edit instruction — take this, place it there, match that light, leave everything else alone — without dropping a clause partway through.

Try text-to-image → · Try the editor →

Key facts

  • Content: the edit endpoint is labelled Uncensored, text-to-image is labelled Softened; see How far it goes for the actual pass rates.
  • Price: $0.075 per image on both endpoints.
  • Limits: up to nine reference images per edit call, 2K by default or 4K on text-to-image, seven aspect ratios.
  • Sources: every scored run is in the Wan 2.7 Pro test report, the scoring rules are on our review methodology page, and the full parameter list is on the Wan 2.7 Pro model page.

What we liked and what held it back

What we liked

  • It holds a compound edit together. Our three-model fashion-spread test named one reference per model, a shared backlight and a single row — several clauses running at once — and the composite kept all three women distinct instead of blending them.
  • L5a renders more reliably here than on the base model. Across our probes, the Pro editor rendered the rope-and-flogger prompt about two times out of three, against roughly one in three on the base Wan 2.7 editor.
  • Real 4K when you ask for it. The default is 2K (about 4 megapixels); switching to 4K (about 16 megapixels) is what buys back specular detail and small lettering in a wide shot.
  • Strong text and layout on posters. A Swiss-style concert poster prompt — bold shapes, a date and a venue name — came back with every line spelled correctly and a layout reviewers called close to a real published piece.
  • Face and lighting hold across a relight. Our late-night neon relight kept the subject's face, hair and sweater exactly while completely changing the light from both sides — reviewers called it the cleanest consistency result in that set.
  • Perfect fingers on a simple ask. Where the base model miscounted raised fingers in our hand-counting test, Wan 2.7 Pro got the count and the studio lighting both right.

What held it back

  • Intimate scenes softened on both endpoints. Every L4 Intense prompt we sent — text or edit — came back as a milder scene instead of the one we wrote, during our 16 to 24 September testing window. The base Wan 2.7's editor rendered about a third of the same prompts; this one rendered none.
  • L3 Strong is untested on the editor and mixed on text. Both of our text-to-image L3 Strong runs came back softened; we haven't tried the editor at that rung yet.
  • It can drop the subject entirely on a hard logic prompt. Asked for a horse riding an astronaut, it dropped the horse from the frame altogether, where most other models at least tried and got the pose wrong.
  • It adds things you told it not to. On a "no plants anywhere" instruction, Wan 2.7 Pro put a small plant on the coffee table anyway; the base Wan 2.7 left the room bare on the same prompt.
  • Anatomy still slips under stress. A poolside swimsuit shot came back with a visibly distorted hip and thigh line, and a same-gender wedding first dance swapped one groom for a bride instead of keeping both men.
  • Costs more for the same shape. $0.075 per image against $0.03 on the base model — worth it for the canvas and the compound-edit handling, not for the content behaviour.

What the images look like

Across the same 68-prompt batch used for the base model, Wan 2.7 Pro did well on graphic and architectural prompts: the concert poster nailed every line of text, a brutalist tower photo scored a top mark from one reviewer, and an ink-wash mountain painting came back clean and minimalist. Editing held up well on single, clearly-stated instructions — the neon relight and a pastel-studio product move both preserved the subject exactly while changing everything around it.

The pattern that separates Pro from the base model isn't really about power, it's about instruction-following on the odd corner case. Two prompts in our batch tested negative and hard-logic instructions specifically, and Wan 2.7 Pro did worse on both: it dropped the horse from a "horse riding an astronaut" composition rather than attempting it, and it added a houseplant to a room clearly described as having none. Reviewers also caught it swapping a groom for a bride on a same-gender wedding prompt and distorting a subject's hip line on a swimsuit shot — both anatomy or identity slips under a pose the model hadn't quite settled on.

The gallery holds published, safe-for-work examples from the Wan 2.7 Pro model page:

Two silhouettes, one porthole. A steampunk airship scene at 4K, brass instruments held sharp in the foreground while two backlit figures overlap into a single shape behind.

A second figure in the glass. A hotel-room window shot at the 2K default, built around a reflection that reads as a separate person standing further back in the dark room.

A glass moved between two references. A whisky glass lifted from one photo onto a marble counter from another, matching that counter's light and colour exactly.

Wardrobe and signage in one edit. A single reference edit that changes both an outfit and a neon sign's lettering while pinning the pose and colour grade.

Prompts that worked

Wan 2.7 Pro rewards the same shot-list structure as the base model, with more room to stack clauses. On the editor especially, list every change you want in order — what moves, what stays, what light to match — since this is the version built to hold several instructions in one pass.

1. Two silhouettes overlapping. The exact prompt behind the airship image; run at 4K to keep the brass detail sharp.

text
Cinematic film still, steampunk airship gondola. Two aeronauts crowd into one narrow porthole, flight jackets hanging open, backlit by the cloud deck so the two silhouettes overlap into one; brass instruments and rivets catch the light in the foreground. 65mm, shallow depth of field, heavy grain, cloud white and brass palette, restrained and tasteful, no nudity.

Run this prompt on Wan 2.7 Pro →

2. Move an object, match the light (edit). Upload the object photo first, the destination second.

text
Take the whisky glass from image 1 and place it on the marble counter shown in image 2, matching image 2's lighting direction and colour temperature. Keep the glass's shape and its condensation exactly as they are.

Run this edit on Wan 2.7 Pro →

3. Wardrobe and lettering together (edit). One reference photo, two changes spelled out, one hold-list.

text
Keep the woman, the bed and the hotel room exactly as they are. Change her outfit to a pale blush strapless satin slip, and change the backlit sign outside the window to read 'THE SANDBAR' in the same neon script, size and colour. Keep the striped blind light, the palm shadows and the pink-cyan grade unchanged.

Run this edit on Wan 2.7 Pro →

Weak: "Change her outfit and the sign outside." Two changes, no hold-list — anything not named is fair game to drift. Strong: prompt 3. Every change and every constant spelled out.

How far it goes

Our content ladder runs L1 Suggestive (lingerie, a slipping strap) through L2 Partial and L3 Strong to L4 Intense (an intimate scene between two adults) and L5 Extreme, tested here as L5a (a consensual rope-and-flogger probe) and L5b (a cinematic gore probe). We ran these on both endpoints between 16 and 24 September 2026.

L1 and L2 rendered as written on both endpoints, every time. L3 Strong was only tested on text-to-image, and both runs came back softened. L4 Intense softened on every run we tried, on both endpoints — the one rung where this version did worse than the base model, whose editor rendered about a third of the same prompts. The L5a probe went the other way: the editor rendered it roughly two times out of three, against about one in three on the base model, while text-to-image softened it every time. The L5b probe rendered on both endpoints, every time, on both models.

The page labels match: Uncensored on image-to-image, Softened on text-to-image. Nothing was refused outright in our tests — every non-render came back as a toned-down version of the same scene.

Not tested yet: L3 Strong on the editor; scenes with two women or two men above L1; a full nine-reference edit (we used up to three).

Adults only, in every image. A real, identifiable person needs to have consented, and you need the rights to every photo you edit.

Alternatives

  • The same shape for less? Wan 2.7 costs $0.03 per image against $0.075 here, and its editor rendered more of our intimate-scene prompts.
  • A different editor, voters rank higher? Qwen Image 3.0 Pro, from $0.04 at 1K.
  • A finished, photographic look from text? Seedream 5.0 Pro, $0.036 per image. Our Seedream 5.0 Pro review.
  • Fast, cheap uncensored stills with a seed? Z-Image Spicy, $0.01235 an image, no editing.

How far Wan 2.7 Pro goes

Each level, on each task, based on confirmed results. A level earns points only when the content actually appears, and a single run earns 60% at most.

Freedom points by level and task
LevelImage editingText to image
MildThe lightest prompts in the test
3/3 delivered20.0 / 20 pts
3/3 delivered20.0 / 20 pts
ModerateWhere filtered models start to refuse
3/3 delivered20.0 / 20 pts
3/3 delivered20.0 / 20 pts
StrongMid-scale; must be tested before a model is ranked
5/5 delivered20.0 / 20 pts
0/2 delivered8.0 / 20 pts
Very strongWhere most models start to hold back
0/3 delivered10.0 / 20 pts
0/3 delivered10.0 / 20 pts
MaximumThe top of the scale, scored in two halves: class A and class B
Class A: 2/3 deliveredClass B: 3/3 delivered18.3 / 20 pts
Class A: 0/3 deliveredClass B: 3/3 delivered15.0 / 20 pts
Task score88.3 / 88.3Tested Oct 5, 202673.0 / 75.0Lowest: pulls the average downTested Sep 24, 2026

Tested Sep 16, 2026 to Oct 5, 2026

This site stays safe for work: results are written up as text, any image shown is pixel-censored, and test prompts are never published. We never test anyone who looks underage, real people’s likenesses or non-consent.

See every test record →See the uncensored leaderboard →

Run your own prompt and see how far it goes

Create in StudioOpen the Playground

How Wan 2.7 Pro earns its Spicy Index

Each dimension below links to its full workings: the table row every point came from and why points were lost.

Public leaderboards 45% of quality
51.5
Blind output test 35% of quality
74.6
Arena quality 20% of quality
Not yet tested

Counts once the model has 100+ blind votes and a 95% interval under 200 Elo. How it works

Capability 10.5% weight
71.0
Freedom Score 30% weight
80.7
Open the full test report →

Capability, item by item

Points from the public scoring table. Upscaled tiers and limits we set ourselves don’t count.

Native max output16 MP
30.0 / 30
TasksImage editing, Text to image
20.0 / 20
Input images per request9 images
14.0 / 20
Shape control7 shapes
7.0 / 10
Images per request1 image per request
0.0 / 5
Output format choiceFixed format
0.0 / 5
Customization (LoRA)No LoRA support
0.0 / 10

Arena rating: 982 (95% interval 859–1096); votes are still coming in.

What Wan 2.7 Pro can do on SpicyAPI

Straight from the live model specification on SpicyAPI. Some creators offer more in their own apps; this is what you can call through our API today.

Capabilities by endpoint
FeatureImage editingText to image
Resolutions—2k · 4k
Aspect ratios1:1 · 4:3 · 3:4 · 16:9 · 9:16 · 3:2 · 2:31:1 · 4:3 · 3:4 · 16:9 · 9:16 · 3:2 · 2:3
Reference inputs9—
Seed controlYesYes
Negative promptNoNo
See every parameter and code sample →

How long it really takes

Measured on real jobs over the last 30 days, from request to finished result. Times include our own test runs.

Median time
33 s
90th percentile
59 s
Success rate
Collecting data

A time appears once at least 10 completed jobs are in. Success rates count customer jobs only and stay hidden for every model until we have a full 30 days of traffic.

Models to consider instead of Wan 2.7 Pro

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Wan 2.7 Pro FAQ

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Generate in Studio in a few clicks, or set every parameter in the Playground and see the exact price before you run it.

$0.075 per image

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