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Comparison

Whisper Model Comparison: From tiny to large

September 2024 • 6 min read

Choosing the right Whisper model is crucial for balancing accuracy and speed. This guide compares all available models with real benchmark data.

Note: This app uses whisper.cpp, which requires significantly less VRAM than the original PyTorch Whisper (~10GB for large) due to GGML optimization.

Quick Comparison

Model Size VRAM Speed Accuracy
tiny 75 MB ~1 GB 32x Good
base 142 MB ~1 GB 16x Better
small 466 MB ~2 GB 6x Great
medium 1.5 GB ~4 GB 2x Excellent
large-v3 3.0 GB ~5 GB 1x Best
large-v3-turbo ⭐ 809 MB ~4 GB 8x Excellent

Detailed Model Analysis

tiny

The fastest model, ideal for quick drafts or when you need results immediately.

75 MB
Model Size
~1 GB
VRAM Required
32x
Relative Speed

Best for: Quick previews, low-resource systems, non-critical content

small

The sweet spot for most users. Great balance of speed and accuracy.

466 MB
Model Size
~2 GB
VRAM Required
6x
Relative Speed

Best for: General use, YouTube videos, podcasts

large-v3-turbo ⭐ Recommended

Optimized for speed while maintaining excellent accuracy. Our recommended choice for most users.

809 MB
Model Size
~4 GB
VRAM Required
8x
Relative Speed

Best for: Professional content, fast processing with high accuracy

large-v3

Maximum accuracy for critical content where every word matters.

3.0 GB
Model Size
~5 GB
VRAM Required
1x
Relative Speed

Best for: Professional broadcasts, legal/medical content, multiple languages

Our Recommendations

For most users: Start with small or large-v3-turbo. They offer the best balance of speed and accuracy for everyday use.

By Use Case

By Hardware