AI avatar model
HeyGen Interactive Avatar
HeyGenThe most polished stock-avatar library, with real-time streaming on top.
HeyGen’s strength is breadth of ready-made avatars and a mature localisation pipeline. If you need a presenter in fourteen languages by Friday, it is the shortest path. Its real-time tier is competent but sits mid-pack on both latency and price.
Sample output
What it actually produces.
One clip is worth more than any benchmark row. Where we have not published a sample yet, the frame below holds the space it will occupy.
Demo clip
No sample of HeyGen Interactive Avatar uploaded yet.
What it animates
Head to toe.
A model that only drives the mouth looks wrong the moment the other person starts talking — nothing on screen moves. Filled means driven, outlined means limited or looped, greyed means static.
- Face
- Full
- Lip-sync
- Full
- Upper torso
- Full
- Hands
- Partial
- Full body
- Partial
Studio avatars gesture from a looped motion library rather than from the speech itself, so hands move but do not always mean anything. Full-body presenters exist in the stock library; the interactive tier is head-and-shoulders.
Source: HumanLike hands-on assessment of HeyGen output
Variants
2 ways to run it.
Same family, different quality/cost rung. Picking the wrong one is the most common way teams overpay.
Interactive
Balancedheygen-interactiveReal-time streaming avatar.
Studio (rendered)
Highheygen-studioPre-rendered video at higher fidelity.
Fit
Two audiences, one model.
The same model is a different proposition depending on what you point it at.
Recruitment fit
Good for employer-brand content, weaker as a live interviewer than Tavus.
Best for
- Employer-brand video
- Multilingual job ads
- Onboarding content
Strengths
- Huge stock library means no replica training
- Excellent video translation for multi-market hiring
Watch out for
- 1.2s latency is noticeable in live conversation
- Stock faces can read as generic to candidates
The numbers
Measured, not asserted.
Published benchmarks
Vendor and independent figures.
- Lip-sync accuracy
- 92%Estimate
- Utterance-to-utterance latency
- 1200 msEstimate
Published as ~92%.
Published as ~1.2s.
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