Seedance 1.5 Pro is a text-to-video AI model developed by ByteDance, designed for joint audio-visual generation that produces high-quality videos with synchronized audio directly from text prompts. It excels in creating smooth motion, cinematic visuals, and immersive sound in a single pipeline, making it suitable for professional-grade content creation. The model supports both text-to-video (T2V) and image-to-video (I2V) tasks, with key strengths in precise multilingual lip-syncing, dynamic camera control, and narrative coherence.

What sets Seedance 1.5 Pro apart is its native audio-visual synthesis paradigm, which generates video frames and audio tracks in one inference pass, ensuring tight temporal synchronization between speech, lip movements, character actions, and camera dynamics. This outperforms traditional "video + TTS" stitching methods, particularly in long dialogues, rapid motions, and dialect-heavy scenarios. Post-training optimizations like Supervised Fine-Tuning (SFT) on high-quality datasets, Reinforcement Learning from Human Feedback (RLHF), distillation, and acceleration frameworks enable over 10x faster inference without significant quality loss, positioning it as a leader in benchmarks like SeedVideoBench-1.5 for prompt adherence, motion vividness, audio quality, and expressiveness.

The underlying technology emphasizes deep cross-modal interaction for multimodal generation, with meticulous engineering for practical deployment. It handles complex prompts involving camera choreography (e.g., dolly zooms, long takes), emotional audio, and multilingual support across English, Chinese, Japanese, Korean, Spanish, and Indonesian, delivering balanced, professional outputs.

• Architecture: Native audio-visual joint generation model with multi-stage distillation, quantization, and parallel inference optimizations
• Parameters: Not publicly specified
• Resolution: 720p/1080p high-fidelity output
• Input/Output formats: Text prompts (T2V), image inputs (I2V); outputs synchronized video clips with audio (4-12 seconds, auto-adapts if length set to -1)
• Performance metrics: Over 10x inference speedup; top-tier in SeedVideoBench-1.5 for audio-visual sync, prompt following, motion stability, audio quality, and expressiveness; leading in multilingual lip-sync and cinematic camera control

• Prioritize prompts with clear dialogue, camera instructions, and audio elements for best synchronization and adherence
• Use high-quality, detailed prompts specifying style, motion, emotions, and languages to leverage multilingual lip-sync strengths
• Avoid extremely high-intensity motion scenarios where stability may degrade
• Balance quality and speed by utilizing acceleration features, but test iterations for complex narratives
• For optimal results, set video length to -1 for automatic adaptation based on narrative rhythm and completeness
• Common pitfalls include over-specifying conflicting elements; refine prompts iteratively to maintain coherence

• Optimal parameter settings: Set video length to -1 for auto-duration (4-12 seconds); use 1080p for professional output
• Prompt structuring advice: Combine camera moves (e.g., "dolly zoom on face"), actions, lighting, emotions, and audio (e.g., "clear Chinese dialect speech with reverb") in one detailed prompt
• Achieve specific results: For lip-sync, specify language and dialect explicitly (e.g., "Spanish dialogue with natural pronunciation"); for cinematic effects, include "long-take tracking shot" or "Hitchcock zoom"
• Iterative refinement strategies: Generate initial short clips, then extend with consistent prompts focusing on one element at a time
• Advanced techniques: Use image-to-video for character consistency; layer prompts like "8-bit pixel art hero running under sunset with retro game music and scanline effects" for stylized outputs

• Generates high-fidelity 1080p videos with native synchronized audio, including speech, sound effects, and music
• Precise multilingual lip-sync across 6+ languages with natural pronunciation, emotional expression, and minimal artifacts
• Advanced cinematic camera control: dolly zooms, long takes, smooth transitions, and dynamic motion
• Strong prompt adherence for complex, multi-layered instructions involving visuals, audio, and narrative pacing
• Excellent audio quality: clear voices, spatial reverb, balanced expressiveness without over-emotion
• Versatile for T2V and I2V, with automatic duration adaptation and 10x+ speed for efficient workflows
• High motion vividness, aesthetic quality, and temporal synchronization in benchmarks

• Dialogue-driven content like interviews or conversations, where tight lip-sync and natural speech excel
• Multilingual projects requiring accurate dialect pronunciation, such as Chinese-heavy or mixed-language videos
• Cinematic short films with advanced camera moves and immersive audio for storytelling
• Music videos and action sequences syncing footsteps, effects, and ambient sounds to visuals
• Professional content creation, including promotional clips and narrative demos, due to fast inference and quality
• Stylized animations, e.g., pixel art games with retro music, as shown in prompt examples
• Image animation for turning static art into smooth clips with audio synchronization

• Excels in audio-visual sync for long dialogues and rapid lip movements, outperforming stitched pipelines per benchmarks
• Users note top-tier natural voices, reduced mechanical artifacts, and realistic spatial audio, especially in Chinese dialects
• Cinematic understanding allows dramatic storytelling with controlled emotional tones for professional stability
• Resource-efficient with 10x speedups via optimizations, suitable for real-world workflows
• Strong in prompt following and visuals, competitive in I2V tasks
• Motion stability improves but may waver in extreme high-intensity scenarios, per evaluations
• Community feedback highlights reliable deployment readiness and benchmark-leading performance

• Motion stability can degrade in extremely high-intensity or complex action scenarios
• Less precise character consistency across multiple shots compared to models with reference image support
• Primarily optimized for short clips (4-12 seconds), with potential challenges in extending to longer formats without extensions