Seedance 2.5 Tests: Save $0.31 per 10-Second Video on ModelGo

Four different production briefs, two API platforms, and actual recorded charges. In this test set, ModelGo charged $8.038059 against OpenRouter’s $9.283320, a 13.41% reduction with matching delivered specifications.

What Is Seedance 2.5?

Seedance 2.5 supports text-driven and reference-led video creation for detailed motion briefs. Its useful production applications include compact narratives, controlled transformations and product assembly sequences.

Test Method and Actual Charges

We ran four distinct briefs: two text-only and two reference-driven, using matching prompts, reference files and requested settings wherever both platforms were accessible. ModelGo costs were matched to settled billing records and OpenRouter costs come from completed responses’ usage data; the table shows model-output charges rounded to six decimals, excluding separately generated reference art.

Cost scope: these are model-call charges, not the cash outlay required to fund an account. They exclude recharge/payment processing fees, including the 5.5% recharge fee used in the separate pricing comparison; percentage differences here compare call charges only.

Four Production Examples

Cargo-bike morning delivery story

Production use: Urban mobility / brand advertising.

Exact prompt

Create a 10-second commercial micro-story in a quiet early-morning neighborhood. A fictional teal electric cargo bicycle carries three secured kraft delivery boxes; an adult rider wears a plain mustard jacket and helmet. Seconds 0–4: a low tracking shot follows the bike around one gentle corner, with realistic wheel rotation and stable box placement. Seconds 4–7: the rider slows and stops beside a small bakery entrance. Seconds 7–10: a restrained wider shot shows the rider handing one box to an adult bakery owner, with the other two boxes still secured. Use warm morning light and natural city sound if audio is generated. No real brands, traffic hazards, text overlays or changing clothing. Deliver one coherent ten-second clip. Avoid speed ramps, unrelated cutaways and abrupt changes in camera direction; preserve the specified subject throughout.

13.41% lower ModelGo charge.

Moss-landscape conservation film

Production use: Environmental brands / storytelling.

Exact prompt

Create a 10-second macro-to-landscape illusion for an environmental brand film. The scene is a miniature moss garden with a shallow stream, tiny fern fronds and one smooth dark pebble. Begin at moss-tip level with a slow low dolly, making the plants feel like a vast forest without changing their actual scale. Seconds 3–7: follow a single water droplet as it slides from a fern tip into the stream, creating small concentric ripples. Seconds 7–10: tilt up gently to reveal the complete garden inside a shallow ceramic tray on a studio table. Keep all plant shapes and stream geography consistent. Soft daylight, restrained natural ambience, no fantasy creatures, text or exaggerated environmental claims. Deliver one coherent ten-second clip. Avoid speed ramps, unrelated cutaways and abrupt changes in camera direction; preserve the specified subject throughout.

13.41% lower ModelGo charge.

Flat-pack furniture assembly visual

Production use: Furniture / product education.

This original reference was used for ModelGo and for the paired OpenRouter request where account access was available.

Exact prompt

Animate the supplied original flat-pack side table into a clear 10-second assembly concept film. Preserve the walnut top, two curved plywood legs, slot geometry and pale background. Seconds 0–3: show the tabletop and two legs separated but aligned above their final positions. Seconds 3–7: the two legs slide into their matching underside slots in a slow readable sequence, with no bending or shape changes. Seconds 7–10: the completed table settles onto the ground and the camera makes a small three-quarter reveal. Use soft studio shadows and realistic wood grain. No hands, extra screws, additional components, text or claims that this is a verified installation instruction. Prioritize mechanical coherence and part identity. Deliver one coherent ten-second clip. Avoid speed ramps, unrelated cutaways and abrupt changes in camera direction; preserve the specified subject throughout.

13.41% lower ModelGo charge.

Paper-crane to packaging narrative

Production use: Packaging / brand film.

This original reference was used for ModelGo and for the paired OpenRouter request where account access was available.

Exact prompt

Create a 10-second square brand film beginning from the supplied original folded-paper crane on an ivory desk. Preserve the paper’s indigo outer face, gold inner face and crisp fold pattern. Seconds 0–4: a slow macro move follows a gentle opening of the wings. Seconds 4–8: the same sheet unfolds in a controlled origami motion and refolds into a small open-top geometric gift box, keeping its two paper colors consistent and its material visibly paper. Seconds 8–10: the camera eases back to a stable overhead hero frame with the open box centered and clean surrounding space. Use quiet paper rustle if audio is generated. No added sheets, disappearing scraps, logos, hands or text. Deliver one coherent ten-second clip. Avoid speed ramps, unrelated cutaways and abrupt changes in camera direction; preserve the specified subject throughout.

13.41% lower ModelGo charge.

How to Calculate the Saving

For outputs with matching delivered specifications, calculate the reduction as (OpenRouter actual charge − ModelGo settled charge) / OpenRouter actual charge × 100. Use the returned dimensions, duration and audio track when deciding whether two outputs are comparable. Across these four briefs, the average difference was $0.311315 per output; repeating that same workload 100 or 1,000 times would mean approximately $31.131529 or $311.315294 less spend. Those are workload projections, not additional billed runs.

Start with the ModelGo API

Install requests and set MODELGO_API_KEY in your environment. The code below uses the endpoint, model ID and parameters from the first real example, with its exact prompt embedded directly. This example submits an asynchronous video job; polling and download steps are described below the code.

import os, requests

prompt = 'Create a 10-second commercial micro-story in a quiet early-morning neighborhood. A fictional teal electric cargo bicycle carries three secured kraft delivery boxes; an adult rider wears a plain mustard jacket and helmet. Seconds 0–4: a low tracking shot follows the bike around one gentle corner, with realistic wheel rotation and stable box placement. Seconds 4–7: the rider slows and stops beside a small bakery entrance. Seconds 7–10: a restrained wider shot shows the rider handing one box to an adult bakery owner, with the other two boxes still secured. Use warm morning light and natural city sound if audio is generated. No real brands, traffic hazards, text overlays or changing clothing. Deliver one coherent ten-second clip. Avoid speed ramps, unrelated cutaways and abrupt changes in camera direction; preserve the specified subject throughout.'
headers = {"Authorization": "Bearer " + os.environ["MODELGO_API_KEY"]}
payload = {'model': 'doubao-seedance-2.5',
 'prompt': prompt,
 'resolution': '720p',
 'duration': 10,
 'aspect_ratio': '16:9',
 'generate_audio': True}
response = requests.post('https://api.modelgo.ai/v1/video/generations', headers=headers, json=payload, timeout=420)
response.raise_for_status()
result = response.json()
print(result)  # Save the returned task ID for polling.

After submission, retain id / task_id from the response and poll GET https://api.modelgo.ai/v1/videos/{task_id} until the task reaches a terminal state. Once successful, download the video using metadata.url from the response.

For first-frame generation on the native content route, send a content array containing the text part and an image_url part with role: "first_frame". For the reference cases here, omit both ratio and aspect_ratio; the reference controls the output geometry.

ModelGo and OpenRouter use different model IDs and media request formats. Reuse the production brief, but adapt the endpoint, reference-image structure, task polling and download handling following each platform’s documented request format.

ModelGo API documentation

Use Seedance 2.5 on ModelGo

To use Seedance 2.5, the model featured in this guide, visit the ModelGo Models page.

Explore Seedance 2.5 on ModelGo

Sources and Further Reading

These references cover model capabilities, interfaces and usage records; the briefs were written independently for this test.

• Official model documentation or family showcase: Model capabilities and creative reference; related family documentation is not a specification guarantee for a different variant.
• OpenRouter API reference: Request conventions and platform differences.
• OpenRouter usage accounting: How usage information is exposed; the amounts in this article come from the recorded test calls.
• OpenRouter model catalog API: Check model IDs and catalog properties before a new integration.
• OpenRouter video generation guide: Media request structure and supported workflow patterns.