Seaweed-7B: ByteDance Unveils a 7B-Parameter Video Model with Real-Time, Audio-Video Generation

• Model Efficiency & Performance

  Seaweed-7B is built with 7 billion parameters, trained over 665,000 H100 GPU hours (≈27.7 days on 1,000 GPUs). This represents one-third the training cost of models like Wan 2.1 (14B). The model’s performance matches or surpasses larger systems across key video tasks, with 62x faster inference than peers.

• Benchmark Results

  Achieved an Elo score of 1047 and 58% win rate in image-to-video tasks — outperforming Wan 2.1 (53%) and Sora (36%). Can generate 720p video at 24fps in real time, enabling live rendering and interactive content.

• Resource Accessibility

  Runs on just 40GB VRAM to produce 1280×720 resolution outputs, democratizing access for independent creators, studios, and SMEs.

• Three Core Technical Innovations

  1. 6-Stage Data Refinement Pipeline: Reduces ineffective data from 42% to 2.9%, boosting training efficiency by 4x.
  2. Architecture Design: Uses a 64× compression VAE with causal 3D convolutions and a hybrid-flow diffusion transformer, speeding convergence by 30% while cutting compute by 20%.
  3. Progressive Training Strategy: Four-stage process — starting with 256p static images and scaling up to 720p HD video, finishing with SFT and RLHF fine-tuning for motion realism and aesthetics.

• DiT Architecture & Adversarial Post-Training (APT)

  Employs a Diffusion Transformer backbone enhanced with APT for faster, higher-quality output. A single inference step generates a 2-second 720p video, streamlining latency-sensitive applications.

• Simultaneous Audio-Video Generation

  Seaweed-7B can synthesize video with synchronized music, ambiance, speech, and lip motion, suitable for virtual avatars, dubbing, and character animation.

• Audio-Conditioned Human Video via Omnihuman

  Integrated with Omnihuman-1, it enables precise gesture-emotion-voice alignment in generated characters, elevating expressiveness and realism.

• Native Long-Form & Multi-Shot Storytelling

  Supports native 25-second single-shot clips and up to 1-minute extended videos. Accepts scene-level and global prompts, maintaining character, style, and environmental continuity across multi-shot narratives.

• Real-Time Generation & 3D World Simulation

  Enables real-time video generation at 720p/24fps, powered by CameraCtrl-II and FLARE/SeedVR to simulate dynamic, view-consistent 3D environments — ideal for interactive storytelling, VR, and games.

• Image-to-Video & Reference-Based Synthesis

  Allows video creation from first/last frame guidance, full image prompts, or reference images (humans, objects, styles) — delivering frame-consistent motion and fine control.

• High-Resolution Upscaling to 2K

  Native 720p videos can be upscaled to 2560×1440 (2K QHD) using a super-resolution module, also usable for restoration of preexisting content.

• Enhanced Physical & Motion Realism

  Post-trained on CGI-rendered videos, the model excels in pose integrity, physics consistency, and natural motion — especially in complex scenes like walking, dance, and interaction.

• Early Developer Adoption & Public Reaction

  Developers on social media report strong results with short dramas, product demos, and virtual characters. ByteDance offers access via Jimeng AI (即梦平台) with API integration and free trial options.

• Enterprise & Educational Applications

  Suited for e-commerce marketing, tourism videos, and animated courseware. Companies can quickly generate customized video assets with minimal hardware and cost.

• Potential Open-Source Impact

  While not yet open-sourced, ByteDance’s transparent publication of research and growing community engagement point to possible future model weight release, which could fuel widespread innovation.

Why This Matters:

Seaweed-7B breaks the mold by proving that size isn’t everything in AI video. With its efficient training pipeline, integrated audio-visual synthesis, and flexible creative tools, the model empowers solo creators and startups as much as it challenges incumbents like OpenAI, Google, and Runway. Its performance unlocks use cases from interactive cinema and education to e-commerce and VR, reshaping what’s possible with affordable, real-time, AI-generated video content.