Concept · Open source vs API
Real-ESRGAN API vs Self-Hosted
Real-ESRGAN is the open-source upscaling standard: excellent quality, free weights, and a non-trivial service layer around it. This is the honest breakdown of what self-hosting really costs vs calling an API.
What Real-ESRGAN is
Real-ESRGAN is the most popular open-source GAN upscaler, with models for faces (GFPGAN-integrated) and general imagery. Quality is genuinely excellent, which is why it is the default baseline for self-hosted upscaling — and why our API is benchmarked against it.
The self-hosting cost breakdown
| Self-hosted Real-ESRGAN | mlslabs API | |
|---|---|---|
| GPU | 1× 8–12 GB VRAM per lane; idle cost between jobs | $0 — workers scale to your queue |
| Speed | Fast on GPU; ~10–60 s/min of 720p video | Parallel workers, similar per-frame speed |
| Ops | CUDA env, model files, queue, retries, monitoring | None |
| Temporal coherence | You add it (Real-ESRGAN is per-frame) | Built-in temporal smoothing |
| Model updates | You track them | Shipped continuously |
| Cost shape | Fixed infra + your time | Per minute of video |
The per-frame problem nobody mentions
Stock Real-ESRGAN upscales frame by frame — each frame independent. On video, that causes flicker: texture that changes between frames. Production pipelines add temporal consistency (optical-flow guidance, blending) — the part of the work that is invisible in demos and essential in deliverables.
When self-hosting wins
- Data must never leave your environment
- GPU fleet already exists with spare capacity
- Full control over every model and setting
- Deep customization of the pipeline
When the API wins
- Batch libraries with variable volume
- No GPU ops team
- Temporal coherence out of the box
- Webhook-driven pipelines
- Pay-per-use vs fixed infra
FAQ
Common questions
Is the API just Real-ESRGAN in the cloud?
The model family is comparable; the API adds temporal coherence, per-content tuning and the whole service layer (queue, retries, webhooks) that self-hosting leaves to you.
How much GPU do I need to self-host?
8–12 GB VRAM for comfortable 1080p work. Upscaling to 4K at batch scale wants a bigger card or more lanes.
Can I migrate from self-hosted to API?
Yes — same inputs/outputs (object storage), same idea, fewer machines. The tutorial pages walk through the swap.
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