Seedance 2.0
Seedance 2.0 is ByteDance’s next-generation multimodal AI video generation model that natively combines audio and video to create highly realistic clips from simple prompts.
What is Seedance 2.0?
Seedance 2.0 is a unified multimodal audio-video generation model developed by ByteDance for high-fidelity, realistic video creation. It is mainly used for text-to-video and story-driven clip generation where creators script cinematic sequences with detailed control over motion, camera, and scene transitions. It is also used in consumer and professional tools like CapCut and Dreamina-style services to turn scripts, reference images, or rough edits into polished short-form content and trailers. Seedance 2.0 follows earlier Seedance 1.0/1.5 video models within ByteDance’s broader SEED family that also includes the Doubao language models and Seedream image generators.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).
| Provider | Input | Output | Cache read /M | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| ByteDance | ~$0.18 | ~$0.50 | — | ~220ms | ~80 tps | ~99.9% |
| OpenAI-compatible Gateway | ~$0.22 | ~$0.60 | — | ~260ms | ~70 tps | ~99.9% |
| Cloud Aggregator X | ~$0.25 | ~$0.70 | — | ~240ms | ~65 tps | ~99.5% |
Try this model
Test Seedance 2.0 right here — free to start.
Suggestions for your first prompt
Code snippet
Call the model through the OpenAI-compatible API.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://inference.example.com/v1"
)
response = client.chat.completions.create(
model="bytedance/seedance-2-0",
messages=[
{
"role": "user",
"content": "Describe this image in one sentence."
}
],
)
print(response.to_json())
{
"model": "bytedance/seedance-2-0",
"messages": [
{
"role": "user",
"content": "Describe this image in one sentence."
}
]
}
5 Core Capabilities
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Text-to-video
Generates coherent, cinematic video clips directly from text prompts, supporting multi-shot narratives with consistent characters, scenes, and camera movements.
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Multimodal Inputs
Accepts combined text, image, audio, and video inputs in a unified model to guide structure, style, and motion of generated videos.
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Native Audio Generation
Jointly generates synchronized soundtracks, effects, and dialogue with videos, enabling frame-accurate lip-sync and environment-aware sound design.
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Interactive Editing
Supports shot-by-shot control and reference-based editing, allowing users to refine pacing, composition, and continuity without manual post-production.
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Cross-language Prompts
Handles prompts and control inputs in multiple languages, enabling creators worldwide to direct and customize video generation workflows.
6 Most Valuable Use Cases
- Text-to-video ads
- Storyboarding clips
- Social media snippets
- Video-based case studies
- Content performance monitoring
- Multimodal video generation
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Intelligent AI Routing
Automatically route each request to the optimal model across providers based on latency, quality, and cost, without changing your integration or redeploying code.
One endpoint, any model -
Cost-Aware Orchestration
Optimize spend with dynamic provider selection, granular usage controls, and model-tier policies so you can keep quality high while staying within strict budgets.
Maximum value per token -
Resilient Fallback Flows
Define automatic failover chains across providers and models, ensuring your production workloads keep running even during outages, rate limits, or degraded service.
No more single points -
End-to-End Observability
Get full visibility into latency, errors, token usage, and provider performance with request-level traces and metrics that plug into your existing monitoring stack.
Debug across providers -
Task-Level Abstractions
Call high-level tasks like chat, tools, or RAG through a unified schema, while LLM.API handles provider quirks, formats, and evolving capabilities under the hood.
Code to tasks, not APIs -
High-Throughput Batch Runs
Process large workloads with efficient batching, concurrency controls, and job-level status APIs, letting you scale evaluations, backfills, and bulk inference safely.
Scale jobs, not stress
When to Use — When NOT to Use
Use it if...
- You need a general-purpose model from a major Chinese provider for broad tasks.
- You need decent chat, Q&A, and summarization for consumer-style applications.
- Your use case involves casual content generation, like marketing blurbs or social posts.
- Your use case involves integrating with the ByteDance ecosystem or China-focused products.
- You need a model likely optimized for mobile-scale deployment and consumer-facing latency.
- You need an additional model to ensemble with others for diversity of outputs.
- Your use case involves experimentation across multiple vendors, including major Chinese LLM providers.
Avoid if...
- You need strong guarantees about data residency and compliance in US or EU jurisdictions.
- Your workload requires state-of-the-art reasoning, coding, or tool-use comparable to top-tier frontier models.
- You need highly transparent documentation, benchmarks, and long-term stability suitable for regulated industries.
- You need best-in-class support, SLAs, and English-language developer ecosystem and examples.
- Your workload requires advanced safety controls, fine-grained policy tuning, or enterprise governance features.
- You need strict assurances that training or inference will not involve cross-border data transfer.
- Your workload requires proven performance on niche domains like biomedical, legal, or financial reasoning.
Frequently Asked Questions
-
What is Seedance 2.0?
Seedance 2.0 is a large language model by ByteDance focused on fast, low-cost text generation for general-purpose applications.
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What is Seedance 2.0 best suited for?
Seedance 2.0 is best for high-volume chatbots, content generation, and lightweight reasoning where throughput and cost efficiency matter more than frontier-level capabilities.
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What context window does Seedance 2.0 support?
Seedance 2.0 supports a 16K token context window, suitable for long conversations, multi-step tools workflows, and moderately long documents.
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What modalities does Seedance 2.0 support via LLM.API?
Through LLM.API, Seedance 2.0 currently supports text input and text output only, without native image, audio, or video support.
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How fast is Seedance 2.0 on LLM.API?
Typical end-to-end latency ranges from 300ms to a few seconds per request on LLM.API, depending on prompt length and concurrency.
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How is Seedance 2.0 priced on LLM.API?
LLM.API exposes Seedance 2.0 with per-token pricing, charging separately for input tokens and output tokens, plus any provider-specific minimums.
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How do I call Seedance 2.0 through LLM.API?
Use the LLM.API chat or completion endpoint with the provider set to "bytedance" and the model name set to "Seedance 2.0".
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How does Seedance 2.0 compare to similar general-purpose models?
Seedance 2.0 typically trades off peak reasoning quality for higher throughput and lower cost than many flagship frontier models.
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Does Seedance 2.0 support tools or function calling via LLM.API?
Yes, Seedance 2.0 can be integrated with tools on LLM.API using the standard function-calling or tool-calling schema supported by the gateway.
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What are the main limitations of Seedance 2.0?
Seedance 2.0 may struggle with complex long-horizon reasoning, precise mathematical proofs, and tasks requiring up-to-date proprietary or domain-specific knowledge.
COMPARE
Competitive Models
-
Seedance 1.5 Pro
Seedance 1.5 Pro is ByteDance’s flagship native joint audio‑video generation model, focused on high‑quality, lip‑synced video with synchronized sound. It is notable for producing short, production‑ready clips from text or image prompts in a single pass.
-
GLM 4.6V
GLM 4.6V is Z.ai’s open-source, large-scale vision-language model that supports images, video, documents, and text with a long context window and native tool use. It is notable for combining high-quality multimodal understanding with function calling and cloud- or local-friendly variants.
-
GLM 5.1
GLM 5.1 is Z.ai’s flagship open-weight Mixture-of-Experts large language model optimized for long-horizon agentic coding and software engineering tasks. It is notable for its very large context window, strong SWE-Bench Pro performance, and open-source MIT licensing.
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