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Let's Enhance vs neural.love

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors. Let's Enhance publishes a starting price ($12); neural.love does not. Both have a free tier. Both ship a public API.

Let's EnhanceUpscales, sharpens and restores photos for print-grade outputneural.lovePhoto and video restoration plus generation on shared credits

Side by side

FactLet's Enhanceneural.love
CategoryImage Upscaling & RestorationImage Upscaling & Restoration
Pricing modelFreemiumFreemium
Starts at$12 month—
Public APIYesYes
PlatformsWeb, APIWeb, API
CompanyLetsEnhance, Inc.Neural Love OÜ
Launched20172020
Last verifiedSep 6, 2026Sep 6, 2026

What our research says

Let's Enhance

The safe browser-based choice when you need resolution for print and do not want to install Topaz or babysit a local upscaler; it is priced per image, so it punishes high-volume use.

Pros

  • Credit rollover up to six months' worth is more forgiving than the usual use-it-or-lose-it model
  • Distinct tools per job (sharpen, restore, unblur, upscale) instead of one catch-all slider
  • Documented API with separate enhancer and upscaler endpoints for production use
  • Running since 2017, so the model quality has had many iterations behind it

Cons

  • Free tier is 10 signup credits and stamps a watermark on output
  • One credit per image makes bulk catalogue work costly next to a one-off desktop licence
  • Top personal plan is 500 credits at $45/month, which is a low ceiling for agencies
  • Newer generative upscalers produce more dramatic detail on heavily degraded sources

neural.love

Come here for restoration and upscaling of old material rather than for generation, which is where this team has been strong since its archival film work. For new image creation, Krea or Magnific will give you noticeably better output per credit spent.

Pros

  • Upscaling and colorization are the original specialty and still the strongest part
  • Single credit balance spans subscription allowance and one-off top-ups
  • Public API with reference documentation for automated pipelines
  • Free public-domain image library alongside the paid tools

Cons

  • Prices and credit rates are not readable without loading the app, which makes budgeting awkward
  • Generation quality sits behind current image-model front-runners
  • Credits are spent per job, so unsatisfying runs still cost you
  • Small team relative to competitors, so feature pace is uneven

Which one fits

Choose Let's Enhance if you need

  • Enlarging product or portfolio shots for large-format print
  • Restoring scanned or damaged family photos without desktop software
  • Teams wiring upscaling into a pipeline through the API instead of a UI

Choose neural.love if you need

  • Restoring, upscaling and colorizing archival photos and footage
  • Cleaning up low-resolution assets before print or video use
  • Batch enhancement automated through the API
  • Users who want one credit pool spanning several media tasks

More comparisons

All neural.love alternatives →Browse all Image Upscaling & Restoration →