Best Promptfoo Alternatives in 2026

OpenAI acquired Promptfoo in March 2026. The core concern for most teams: Promptfoo's primary job was evaluating and red-teaming AI applications — and the company grading your AI outputs is now owned by one of the providers those outputs come from.

What Promptfoo was doing for your team

Promptfoo is a testing and red-teaming tool — it lets you run automated evals across LLM providers, test prompts against assertions, scan for vulnerabilities, and integrate safety checks into CI/CD pipelines. It runs locally, supports a wide range of LLM providers, and never required a managed service. That combination of vendor neutrality and depth is what the acquisition put in question.

Two different problems

Teams searching for alternatives are usually solving one of two things — or both:

Eval and red teaming

Testing prompt outputs, checking for regressions, scanning for vulnerabilities before production. Promptfoo's core territory.

Production prompt management

Versioning prompts, deploying changes without code releases, tracking what each AI feature costs, observing live behaviour. The layer that comes after testing.

Promptfoo covered the first. Most teams were handling the second with a mix of environment variables, Git, and guesswork. These are different tools for different jobs — and the right answer after the acquisition depends on which problem you're actually solving.

Endprompt — for production prompt management

Endprompt is the infrastructure layer that sits between your application and the LLM. Your app calls one stable endpoint; Endprompt handles prompt rendering, the LLM call, caching, and logging. It's built for the part of the lifecycle that comes after your prompts have been tested.

  • Stable API endpoint — your app calls the same URL forever; prompts and models are configuration, not code
  • No-deploy prompt updates — change, test, and promote prompt versions from the UI without touching your application
  • No LLM provider dependency in your app — switch models without a code change
  • Cost tracking by feature — spend tracked at the endpoint level, so you know what each AI feature actually costs
  • Automatic caching — repeated queries cached with no code changes; up to 67% cost reduction in repeated-query scenarios
  • Full observability — logs, latency, token usage, and estimated cost per request, all by endpoint

Best for: Teams who want prompts managed as production infrastructure — versioned, observable, and fully decoupled from application code.

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Garak — for vendor-neutral red teaming

Open-source vulnerability scanner owned and maintained by NVIDIA. Runs probes across a taxonomy of LLM failure modes — prompt injection, jailbreaking, hallucination, data leakage, and toxicity. CI/CD-compatible and model-agnostic. NVIDIA has no commercial stake in which language model you choose.

Best for: Teams that need independent, automated red teaming with no LLM vendor conflict.

Giskard — for open-source AI red teaming

Independent open-source AI red teaming and security platform. Covers hallucination testing, prompt injection detection, and RAG evaluation. European company, no frontier-model parent.

Best for: Teams that want open-source, independent red teaming with strong RAG testing support.

Which one is right for you?

  • You need production prompt management — versioning, stable API, cost tracking → Endprompt
  • You need vendor-neutral red teaming and vulnerability scanning → Garak
  • You need open-source red teaming with RAG support → Giskard
  • You need both layers → Endprompt for production management, Garak or Giskard for testing

Endprompt

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