Wan 2.7 R2V Tutorial
Wan 2.7 is the one video model out of 37 that gives you a seed, a negative prompt and prompt extension. That changes how you can iterate.
TL;DR
Wan 2.7 is the only one of the 37 video generation models exposing a seed and prompt extension, and one of only two with a negative prompt, alongside prompt, duration, ratio and resolution. It sits at PREMIUM and supports text, image and reference to video. A fixed seed lets you change one prompt clause and see what that clause did, rather than what it did plus a different random draw. Wan 3.0 gains audio generation but loses the seed and negative prompt.
Wan 2.7 is the only video model on the platform with a seed.
Out of 37, it is the one entry that lets you set a seed and switch on prompt extension, and one of only two with a negative prompt. Everything else gives you prompt, duration, aspect ratio and resolution, and that is that.
If you have been hunting for repeatability in AI video, this is where it lives. Not in a strength slider, which does not exist on Wan 2.7 or anywhere else.
What Wan 2.7 actually accepts
Seven parameters, and three of them are unique to it:
prompt. The description.
duration, ratio, resolution. The standard shape controls. Note it uses ratio where most models use aspect_ratio, a quirk worth knowing if you are calling it through the API.
negative_prompt. What to keep out. The real lever for removing artifacts, shake or unwanted objects.
prompt_extend. Lets the model elaborate your prompt before generating.
seed. The same seed with the same inputs gives you the same generation.
It sits at PREMIUM tier and supports text-to-video, image-to-video and reference-to-video.
Why the seed matters more than it sounds
Generation is stochastic. Run the same prompt twice and you get two different clips, which is fine when exploring and maddening when you are trying to change one thing.
With a fixed seed you can change the prompt and see what the prompt did, rather than what the prompt plus a different random draw did. That turns guesswork into something closer to iteration.
Practical uses:
Isolate a prompt edit. Lock the seed, change one clause, compare. Now the difference you see is attributable.
Reproduce an approved take. Record the seed alongside the prompt and you can come back to that exact result weeks later.
Generate variations deliberately. Keep the prompt, change the seed, and you get genuine alternatives of the same idea rather than accidental ones.
Every other model on the platform makes you re-roll blind.
Using the negative prompt
The second thing Wan 2.7 gives you that most models do not.
Negative prompts work best on concrete nouns and visible defects, not abstractions. "Blurry, extra fingers, watermark, text overlay, camera shake" is useful. "Bad quality, ugly" is close to noise.
Put things there rather than in the main prompt. Writing "no text on screen" in the positive prompt often produces text, because the model weighs the concept more than the negation. That is exactly what the negative field is for.
Reference-to-video with Wan 2.7
It is one of the thirteen models that accept a character reference, through reference to video.
There is no reference strength value on Wan 2.7 or anything else. What decides whether a character holds is the reference image: frontal or three-quarter, large in frame, evenly lit, sharp, and the exact same file across every generation.
Combine that with a fixed seed and you have the most controlled setup available here: same character, same random draw, one variable at a time.
Where Wan 2.7 sits in the family
Wan 2.6 Flash. STANDARD tier, text-to-video and image-to-video, no reference support.
Wan 2.7. PREMIUM, adds reference-to-video plus the seed, negative prompt and prompt extension.
Wan 3.0. ULTRA, text, image and reference to video, with audio generation. No seed.
Note the trade: moving up to Wan 3.0 gains you audio generation but loses the seed and negative prompt. Higher tier does not mean strictly more control, which is unusual and worth knowing before you upgrade out of the features you were relying on.
A broader comparison is on the Wan alternatives page.
What is not real
No motion strength. Not 0.65, not a 0.40 to 0.85 range, not a default. No model has it.
No fixed input resolution requirement. You are not obliged to supply a 1024x576 reference.
No frame rate control. You do not set 24 fps.
No published generation times or per-model quality scores. Those vary with load and content.
A workflow that uses what is actually there
- Write the prompt, and put defects and unwanted elements in the negative prompt rather than negating them in the positive one.
- Generate a few times with the seed unset, to find a result whose overall shape you like.
- Note that seed.
- Lock it, and iterate the prompt one clause at a time. Now every change is legible.
- Once the prompt is right, unlock the seed if you want variations of the finished idea.
That loop is not available on any other video model here, which is the honest reason to reach for Wan 2.7 over something cheaper.
The catalog is at Models, each generation is quoted before it runs, and pack prices are on the pricing page.
Frequently Asked Questions
What parameters does Wan 2.7 accept?▾
Seven: prompt, duration, ratio, resolution, negative_prompt, prompt_extend and seed. It uses ratio where most models use aspect_ratio, which matters when calling it through the API. The last three are unique to it among the 37 video generation models.
What motion strength should I set on Wan 2.7?▾
There is no motion strength on Wan 2.7 or any other model. Values like 0.65, or a range of 0.40 to 0.85, appear in guides but no model exposes such a parameter. The controls that do exist are listed in its parameter set.
Why does the seed matter?▾
Generation is stochastic, so running the same prompt twice gives two different clips. With a fixed seed you can change one prompt clause and see what that clause did, rather than what it did plus a different random draw. It also lets you reproduce an approved take weeks later by recording the seed alongside the prompt.
How should I write a negative prompt?▾
Use concrete nouns and visible defects rather than abstractions. "Blurry, extra fingers, watermark, text overlay, camera shake" works; "bad quality, ugly" is close to noise. Put unwanted things there rather than negating them in the main prompt, since writing "no text on screen" positively often produces text.
Should I upgrade from Wan 2.7 to Wan 3.0?▾
Only if you need audio generation. Wan 3.0 sits at ULTRA and adds audio, but loses the seed and negative prompt. Higher tier does not mean strictly more control here, so check you are not upgrading out of the features you were relying on.
Does Wan 2.7 need a specific reference image size?▾
No. There is no fixed input resolution requirement such as 1024x576. What matters is the quality of the reference: frontal or three-quarter, large in frame, evenly lit, sharp, and the exact same file across every generation.
What is the best iteration loop on Wan 2.7?▾
Generate a few times with the seed unset to find a result whose shape you like, note that seed, lock it, then iterate the prompt one clause at a time so every change is legible. Unlock the seed at the end if you want variations of the finished idea.
