Client-side rendering
The client loads the avatar resource and applies motion data locally. Product UI, background, and avatar can be composed in the same application surface.
Architecture comparison
Client-side vs server-side AI avatar rendering
Client-side rendering moves avatar composition to the user's device and can reduce streamed media. Server-side rendering centralizes compute and visual output but requires cloud rendering and media delivery. The target client and session economics should decide.
Verified Aug 3, 2026Decision-ready guidePrimary sources
Decision matrix
Compare the complete path.
Do not compare isolated numbers unless the definitions, inputs, environment, and included services match.
| Decision area | Client-side rendering | Server-side rendering |
|---|---|---|
| Compute placement | Client GPU/graphics runtime | Cloud GPU or render server |
| Network payload | Assets plus motion/control data | Encoded media stream |
| Visual composition | Integrated with local UI | Composed before delivery |
| Client requirement | Supported graphics and memory | Media decoding and connection |
| Operational cost | Distributed client compute | Central compute and bandwidth |
| Version control | Client SDK and asset rollout | Central renderer rollout |
| Best fit | Owned clients and high session volume | Thin clients and centralized visuals |
How it works
Two different operating models.
Architecture decides which team owns rendering, transport, recovery, and the surrounding AI product.
Server-side rendering
Cloud infrastructure renders the final frames, encodes them, and sends media to the user. The output can be controlled centrally across thinner clients.
Best fit
Choose for the system you can operate.
The best option is the one whose responsibilities match your product, client, network, and team.
Choose Client-side rendering when…
- Product controls the application client
- Local composition is valuable
- Network traffic is constrained
- Cloud GPU cost must stay low
Choose Server-side rendering when…
- Target clients cannot render reliably
- Central output consistency dominates
- Existing video infrastructure is mature
- Cloud cost is acceptable
Limitations and unknowns
Client-side rendering needs device testing and asset lifecycle management. Server-side rendering needs capacity planning and network resilience. Neither removes observability work.
Build a controlled evaluation.
Use one workload and record both user experience and operational responsibility.
1. Evaluation stepBenchmark the lowest supported client.
2. Evaluation stepCompare cold-start asset loading with stream startup.
3. Evaluation stepModel concurrent cloud GPU requirements.
4. Evaluation stepTest visual recovery after network changes.
- Define the user job and acceptable fallback.
- Use the same input, session duration, and client.
- Record latency, traffic, compute, errors, and recovery.
- Compare total operating cost, not only list price.
Evidence
Sources and freshness.
Last verified Aug 3, 2026. Recheck implementation details when SDKs or plan terms change.
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