AI caption and subtitle generator that adds captions to videos in seconds with no watermark
Open-source SDXL-based AI model for native high-resolution anime art generation
Stage
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Founded
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Based in
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Pricing model
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Open source
Pricing
Free: 30 minutes of captions per month, 1080p MP4 export up to 3 minutes, 8 caption styles, SRT/VTT/TXT downloads up to 30 minutes, free translation into 100+ languages. Pro: $6.99/month (limited-time price, normally $9.99) or $59/year, unlimited captions on videos up to 90 minutes, all 22 caption s
Free for personal and research use; prohibits closed-source proprietary monetization
Key features
Automatic speech transcription in 100 languages with automatic language detection
SRT, VTT and TXT subtitle file downloads
Free translation into 100+ languages
Copy caption style from screenshot functionality
Bilingual captions showing two languages simultaneously on Pro
Video processing entirely in browser with audio-only server transmission for privacy
Word-level timing synchronization for precise caption timing
Native 1536x1536 high-resolution generation without upscaling
Hybrid Prompting System combining natural English and Danbooru tags
Stable text encoder fine-tuning for superior concept understanding
Trained on comprehensive Danbooru2023 dataset
Full compatibility with ComfyUI, Automatic1111, Forge, and Draw Things
Superior anatomy rendering with flawless hands and character details
V-Prediction architecture for enhanced dynamic range and contrast
Highly flexible base canvas for LoRA training and custom checkpoints
What makes it different
Fastest among 10 tested caption tools, 6.7× faster than CapCut and 4.7× faster than VEED
Highest accuracy with 5.7% word error rate in October 2026 accuracy test of 8 caption tools
Video stays entirely private with only audio sent for transcription
Only open-source SDXL model natively trained at 1536x1536 resolution
Stylistically neutral untuned base canvas unlike Pony Diffusion
Continuous rapid iterations from v0.1 to v3.5 with aggressive optimization
Thousands of compatible community-trained LoRAs and derivatives