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Seedance 2.0 Fast

  • Text Generation

Seedance 2.0 Fast is ByteDance’s speed‑optimized variant of the Seedance 2.0 multimodal video generation model, trading some visual fidelity for much faster, lower‑cost rendering. It preserves the full text‑, image‑, audio‑, and video‑to‑video capabilities with native synchronized audio.

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Providers Comparison

Speed

Output tokens per second · Higher is better

246
97
92
91
90
80
60
27
LLM API
SiliconFlow (FP8)
GMI
CoreWeave
Novita
DeepSeek
Parasail (FP8)
DeepInfra (FP4)

End-to-End Response Time

Seconds · Lower is better

65.1
8.1
19.8
20.4
20.9
23.1
24.6
30.6
LLM API
SiliconFlow (FP8)
GMI
CoreWeave
Novita
DeepSeek
Parasail (FP8)
DeepInfra (FP4)

Price

USD per 1M tokens (blended) · Lower is better

65.1
8.1
19.8
20.4
20.9
23.1
24.6
30.6
LLM API
SiliconFlow (FP8)
GMI
CoreWeave
Novita
DeepSeek
Parasail (FP8)
DeepInfra (FP4)

About the model

What is Seedance 2.0 Fast?

Seedance 2.0 Fast is a high‑speed version of ByteDance’s Seedance 2.0 native multimodal audio‑video generation model designed for low‑latency video creation. It is mainly used for rapid prototyping, social media clips, ad and creative batch production, and other high‑volume pipelines where fast turnaround is more important than maximum detail. It is also used for iterative prompt exploration, storyboards, and draft renders before switching to higher‑quality variants. It belongs to the Seedance 2.0 model family as the fast, cost‑efficient companion to the standard full‑quality model.

Model capabilities

5 Core Capabilities

  • Text-to-video generation

    Generates short cinematic videos directly from natural language prompts, including camera motion and synchronized native audio output.

  • Image-to-video animation

    Animates one or more reference images into coherent video clips, preserving subject identity, style, and overall visual consistency.

  • Multimodal video editing

    Edits and extends existing videos using textual instructions plus optional image, video, and audio references to guide changes.

  • Audio-aware generation

    Jointly generates or conditions on audio to produce frame-accurate sound effects, speech, and lip-sync aligned with video content.

  • Fast iterative prototyping

    Optimized for rapid, lower-cost video generation, enabling quick experimentation and high-volume content workflows compared to standard tier.

Use cases

6 Most Valuable Use Cases

  • Rapid ad creatives
  • Storyboarding drafts
  • Social clip generation
  • Game trailer prototypes
  • Video A/B testing
  • Educational explainer videos

Transparent pricing

Cost Comparison

LLM API offers the lowest cost and latency for Seedance 2.0 Fast–class models across providers.

Provider Region Latency Throughput Uptime Input ($/1M) Output ($/1M) Context
LLM API BEST Global 80ms 70 tps 99.99% $0.10 $0.10 128K
ByteDance Global ~140ms ~45 tps ~99.9% ~$0.40 ~$0.40 ~64K
OpenAI Global ~160ms ~40 tps 99.9% ~$0.60 ~$0.80 ~128K
Anthropic US East ~170ms ~35 tps 99.9% ~$0.55 ~$0.75 ~200K

Performance benchmarks

Technical Specifications

Metric Seedance 2.0 Fast GPT-4o Mini (Fast) Claude 3.5 Haiku
Avg Latency ~180ms ~250ms ~220ms
Context Window 128K 128K 200K
Input Price ($/1M) $0.15 $0.15 $0.25
Output Price ($/1M) $0.60 $0.60 $0.80
Max Output Tokens 4K 4K 4K
Throughput ~120 tps ~100 tps ~90 tps
Uptime 99.9% 99.9% 99.9%

30-day usage via LLM API

7.8B
Prompt tokens processed (30 days)
26M
Completion tokens generated (30 days)
3.4M
API requests served (30 days)
99.8%
Average API uptime (30 days)
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Architecture & Integration

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Unified AI Routing

    Automatically route each request to the optimal model across providers based on latency, cost, and quality—no code changes, just smarter defaults.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with fine-grained pricing visibility, per-model limits, and smart routing that prefers cheaper equivalents when quality and latency stay within your targets.

    Slash AI spend safely.

  • Automatic Fallbacks

    Define fallback chains once and recover gracefully from provider outages, rate limits, or timeouts without rewriting client logic or shipping emergency patches.

    No more model downtime.

  • End-to-End Observability

    Trace every request across providers with logs, metrics, and structured events so you can debug failures, tune prompts, and prove SLAs from a single dashboard.

    See every token move.

  • Task-Level Abstractions

    Call high-level tasks—chat, tools, retrieval, evaluations—instead of raw endpoints, letting LLM.API map them to the right models and providers behind the scenes.

    Think tasks, not models.

  • High-Throughput Batching

    Batch thousands of inferences per call with provider-optimized concurrency, dramatically lowering per-request cost while keeping latency predictable and manageable.

    Scale to millions easily.

Decision guide

When to Use — When NOT to Use

Use it if...

  • You need a fast, lower-cost model from ByteDance for general-purpose text tasks.
  • You need quick responses for chatbots or virtual assistants with moderate reasoning depth.
  • Your use case involves high-volume user interactions where throughput and latency matter most.
  • Your use case involves lightweight content rewriting, summarization, or classification at large scale.
  • You need a pragmatic model for A/B testing alongside heavier, more capable LLMs.
  • Your use case involves prototyping apps where speed of iteration outweighs peak model capability.

Avoid if...

  • You need state-of-the-art reasoning or coding performance comparable to frontier flagship models.
  • You need reliable handling of extremely long contexts, such as full-book analysis.
  • You need best-in-class instruction following on complex, multi-step enterprise workflows.
  • Your workload requires highly specialized domain reasoning, such as advanced legal or medical tasks.
  • Your workload requires top-tier multilingual performance, especially for low-resource or niche languages.
  • You need robust tool-use and agentic planning beyond simple, shallow decision-making chains.

FAQ

Frequently Asked Questions

  • What is Seedance 2.0 Fast?

    Seedance 2.0 Fast is a ByteDance language model variant optimized for low-latency, cost-efficient text generation via the LLM.API gateway.

  • What is Seedance 2.0 Fast best suited for?

    Seedance 2.0 Fast is best for high-throughput chatbots, lightweight assistants, and backend services where response speed and cost are more important than peak quality.

  • What is the context window of Seedance 2.0 Fast?

    Seedance 2.0 Fast supports a context window of up to 32K tokens for combined input and output through LLM.API.

  • How fast is Seedance 2.0 Fast on LLM.API?

    Seedance 2.0 Fast is tuned for low latency and typically returns the first tokens in well under a second for standard chat prompts.

  • What modalities does Seedance 2.0 Fast support?

    Seedance 2.0 Fast is a text-only model that accepts text prompts and returns text completions.

  • How is Seedance 2.0 Fast priced on LLM.API?

    Seedance 2.0 Fast is offered as a budget-friendly tier on LLM.API with per-token billing for prompts and completions.

  • How do I call Seedance 2.0 Fast through LLM.API?

    Specify the model name "Seedance 2.0 Fast" in your LLM.API request along with your API key and a standard chat or completion payload.

  • How does Seedance 2.0 Fast compare to more powerful Seedance variants?

    Seedance 2.0 Fast is generally cheaper and faster but slightly weaker on complex reasoning, coding, and long-context tasks than larger Seedance models.

  • Does Seedance 2.0 Fast support streaming responses on LLM.API?

    Yes, Seedance 2.0 Fast supports server-sent events streaming so you can start processing tokens as they are generated.

  • What are the main limitations of Seedance 2.0 Fast?

    Seedance 2.0 Fast may hallucinate facts, struggle with highly specialized domains, and underperform larger models on multi-step reasoning or long-document analysis.

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