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testcritic

Mockoon vs Gretel.ai

Feature checklists rarely decide anything. What decides it is the pricing metric, who has to write the tests, and which limitation you can live with.

Entry price

From $100 per month (Team, billed annually, up to 5 members)

Free tier

Quote on request

Quote only

What drives the bill

The metric that actually scales your invoice.

Free locally and forever; the paid cloud tier adds hosted mocks and team sync. Team covers 5 members, 3 cloud-deployed mocks and 100k calls a month, with Enterprise on a quote. Work emails get a 14-day trial, others 7 days with a card.

The old credit-based self-serve tier is gone. The successor microservices are licensed through NVIDIA AI Enterprise; NeMo Data Designer can be tried on build.nvidia.com.

Free tier

The desktop app and CLI are free and open source.

Open source

MIT

Self-hostable

No-code authoring

Languages

JavaScriptCodeless
PythonCodeless

Platforms

API
API

Fits teams

Solo / side projectStartupScale-up / mid-market
Enterprise

Adoption

Widely used

Mockoon · since 2017

Emerging

NVIDIA (formerly Gretel) · since 2019

Strengths

  • Genuinely a minute from download to a working mock API.
  • Dynamic templating with faker-style helpers produces realistic responses.
  • Proxy mode mocks only the routes you need and passes the rest through.
  • Formal differential-privacy guarantees rather than best-effort masking, now via DP-SGD in NeMo Safe Synthesizer.
  • Synthetic data preserves statistical relationships useful for analytics and model training.
  • Backed by NVIDIA's platform investment rather than a single startup's runway.

Limitations

  • Desktop-first; sharing mocks across a team needs the paid cloud or a committed config file.
  • HTTP only.
  • Less suited to complex stateful behaviour than WireMock.
  • No longer buyable as Gretel — you are procuring NVIDIA AI Enterprise, which is far heavier than the old self-serve signup.
  • Model training adds time and cost compared to rule-based masking.
  • Safe Synthesizer trains on a real dataset, so it does not help with greenfield data that does not exist yet.

Best for

Front-end developers unblocking themselves while a backend is still being built.

Regulated enterprises already standardising on NVIDIA AI Enterprise. Teams that wanted Gretel's self-serve tier should look at Tonic or Neosync instead.

Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.