Last Updated: January 16, 2026 | Review Stance: Independent testing, includes affiliate links

TL;DR - GFPGAN 2026 Review

GFPGAN remains a timeless open-source classic in 2026 for real-world face restoration, delivering impressive detail recovery on old, blurry, or AI-generated faces. Free and powerful with GAN priors, though development stopped in 2022—still widely used via demos and integrations.

GFPGAN Review Overview and Methodology

GFPGAN (Generative Facial Prior GAN) is an open-source project by Tencent ARC Lab (2021) for practical blind face restoration. It uses pretrained face GANs (like StyleGAN2) to recover details from real-world degraded images without prior knowledge of damage type.

This 2026 review assesses its enduring relevance through testing on old photos, low-res portraits, and AI-generated faces—evaluating restoration quality, speed, ease of use, and comparisons to modern tools.


Here are some impressive before-and-after examples of GFPGAN in action, showcasing its ability to revive old and damaged photos:

 

 

These demonstrate dramatic improvements in facial clarity, texture, and naturalness.

Old Photo Revival

Restore family archives, vintage portraits.

AI-Generated Fixes

Enhance faces from Midjourney/Stable Diffusion.

Low-Res Upscaling

Sharpen blurry portraits with detail recovery.

Professional Editing

Batch process for archives or retouching.

Core Features of GFPGAN

Key Tools & Capabilities

  • Blind Face Restoration: Handles unknown degradations (blur, noise, compression, low-res).
  • Generative Priors: Leverages StyleGAN2 for natural, high-fidelity faces.
  • Multiple Versions: v1.3 (natural), v1.4 (detailed identity), clean variants.
  • Upscaling & Background: Optional x2-x4 upscale + Real-ESRGAN for non-face areas.
  • Colorization & Alignment: Built-in options for old B&W photos.
  • Easy Inference: Python script for batch/whole-image processing.

User Experience Highlights

  • Simple CLI/Python usage, no GUI needed
  • Colab/Hugging Face/Gradio demos for zero-install
  • High-quality results on real-world cases
  • Customizable (strength, version, upscale)
  • Open-source & community-supported

GFPGAN Functionality & Performance

In 2026, GFPGAN continues to impress with natural-looking restorations, excellent detail recovery (eyes, skin, hair), and good identity preservation—even on heavily degraded inputs. It outperforms many general enhancers in face-specific tasks, though newer tools may edge it in speed or extreme cases.

Key Advantages in Performance

Natural Results
Detail Recovery
Blind Restoration
Free & Open
Customizable

GFPGAN Use Cases

Ideal Scenarios

  • Family photo archives & old portraits restoration
  • Fixing AI-generated faces (Midjourney/Stable Diffusion)
  • Low-res historical images enhancement
  • Batch processing for digital archivists
  • Integration in custom pipelines (e.g., with Real-ESRGAN)

Access Options

GitHub Local Install

Colab / Hugging Face

Online Demos

Integrations

GFPGAN Pricing & Plans

Free / Open-Source

$0 Forever

Full access

  • Complete code & models
  • Local/Colab usage
  • Batch processing
  • Community support

Online Demos

$0 (Free tier)

Quick tests

  • Hugging Face Gradio
  • Replicate / Colab
  • Limited uploads/speed
  • No install needed

As of January 2026, completely free & open-source (Apache 2.0). No paid plans; optional cloud costs for heavy local use.

Pros & Cons: Balanced Assessment

Strengths

  • Outstanding natural face recovery
  • Excellent on real-world degradation
  • Free, open-source, customizable
  • Multiple model variants
  • Easy demos & integrations
  • Still relevant in 2026

Limitations

  • No updates since 2022
  • May need tweaks for latest PyTorch
  • GPU required for fast processing
  • Occasional artifacts in extreme cases
  • No native GUI

Who Should Use GFPGAN?

Best For

  • Photo archivists & historians
  • AI art users fixing faces
  • Developers & researchers
  • Budget-conscious restorers
  • Old family photo enthusiasts

Consider Alternatives If

  • You need active updates & GUI
  • Want cloud-based easy service
  • Require video or advanced features
  • Prefer newer models (e.g., CodeFormer)

Final Verdict: 8.9/10

GFPGAN is a legendary open-source tool in 2026—still delivering top-tier face restoration results with natural, detailed outputs. Its free nature and proven performance make it essential for anyone restoring old photos or fixing AI faces, despite the lack of recent updates.

Restoration Quality: 9.4/10
Ease of Use: 8.2/10
Value for Money: 10/10
Maintenance: 6.5/10

Experience Classic AI Face Restoration

Restore your old photos or enhance AI faces for free—download the code or try online demos today.

Visit GFPGAN GitHub Repository

Completely free & open-source as of January 2026.

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