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Balanced — mixed-30-v2

The recommended default. Analyzes 30 frames (1 second of video) for the best overall accuracy with minimal latency.

At a Glance

Model IDmixed-30-v2
Frames required30
Capture time~1 second at 30 FPS
Avg response time~3s
Security levelStrongest

When to Use

  • Standard KYC / identity verification — the best default for most use cases
  • Account creation where you need solid protection without excessive friction
  • Financial services where regulatory requirements demand robust liveness checks
  • Any flow where 1 second of capture is acceptable

Performance

Based on evaluation across 1,960 test videos (9 attack types, held out from training):

EER4.0%
AUC0.991
Balanced accuracy95.7%
Avg response (fast-check)~3s

Per-Attack Detection

Attack Type Detection Rate
Physical spoofing 98.3%
Deepfakes 95.6%
Screen replay 92.6%
Faceswap 80.3%

Operating Points

The tradeoff between security and user friction at different thresholds:

Max BPCER (user rejection) APCER (attack pass-through)
1% 12.8%
5% 3.7%
10% 1.6%
Max APCER (attack pass-through) BPCER (user rejection)
1% 10.6%
5% 3.1%
10% 1.2%

What this means

At the EER operating point, 96% of attacks are correctly blocked and 96% of legitimate users pass. The 30-frame model delivers the best accuracy across all variants — the recommended choice for production.

Tradeoffs

  • Best overall accuracy — 4.0% EER and 0.991 AUC, the top performer across all variants
  • Strong across all attack types — 95%+ detection for deepfakes and physical spoofing
  • Only 1 second of capture — acceptable for virtually all verification flows
  • Best calibrationconfidence scores most accurately reflect true probabilities (lowest ECE and Brier score)

Integration

{
  "session_id": "550e8400-e29b-41d4-a716-446655440000",
  "model": "mixed-30-v2",
  "source": "live",
  "frames": [
    { "index": 0, "timestamp_ms": 0, "pixels": "..." },
    { "index": 1, "timestamp_ms": 100, "pixels": "..." },
    ...
  ]
}

Capture 30 frames at 30 FPS (1 second total).