Promptfoo Alternatives in 2026 (After the OpenAI Acquisition)

OpenAI acquired Promptfoo in March 2026. If you're evaluating alternatives, here's how to choose based on why you used it.

On March 9, 2026, OpenAI announced it was acquiring Promptfoo. If you missed it: Promptfoo was the open-source LLM testing framework that ~25% of Fortune 500 engineering teams had quietly adopted for red-teaming and CI/CD assertion testing. Now it's being pulled into OpenAI's Frontier platform.

Every "Promptfoo alternatives" article you'll find was written before that happened. None of them address what actually changed — or help you figure out which alternative fits your specific use case. That's the gap this article fills.

Why Promptfoo users are looking for alternatives now

The acquisition doesn't kill Promptfoo. It stays open source under the current license, and your existing YAML test suites still run. The concern is subtler.

When an independent OSS project gets absorbed into a large platform, a predictable pattern follows: the roadmap aligns with the acquirer's priorities, not the community's. Issues slow down. Contributors move on. In Promptfoo's case, the acquisition was driven by its red-teaming and enterprise security capabilities — the exact features OpenAI needed for Frontier. Output testing for non-OpenAI models? That's not the acquirer's interest.

If you're running LangChain pipelines, using Anthropic models, or building on an open-source stack, the maintenance trajectory matters. Now is a reasonable time to evaluate alternatives, not because Promptfoo broke, but because you shouldn't discover that it did mid-production.

What were you using Promptfoo for?

This is the question no other alternatives guide asks — and it's the only one that matters. Promptfoo did several different things, and the alternatives map is completely different depending on which part you relied on.

Pick your path:

• Red-teaming / adversarial security testing → Garak or Microsoft PyRIT
• Output assertion testing in CI/CD (YAML-based) → DeepEval or LangSmith
• Prompt quality scoring / structural evaluation → PromptEval
• Production monitoring + team collaboration → Braintrust
• Enterprise release governance → Adaline
• LangChain / LangGraph ecosystem testing → LangSmith

If you were using Promptfoo for two or more of these, you may need two tools. That's not a failure — it's just that Promptfoo was unusually broad for a single open-source project.

The 6 best Promptfoo alternatives — compared

The 6 alternatives in detail

1. PromptEval — best for structural prompt scoring

PromptEval takes a different angle from Promptfoo. Where Promptfoo tested what a prompt produces, PromptEval scores what a prompt is — its structural quality across 4 dimensions: clarity, specificity, structure, and robustness.

The use case is catching prompt problems before they reach production. Feed it a prompt, get a 0-100 score broken down by dimension, and get exact recommendations on what to fix. No API key needed. No CLI. Opens in a browser tab.

Real data from the platform: the top-scoring prompt on the leaderboard sits at 72/100. Specificity fails 2.3× more often than any other dimension — most prompts leave too much to the model's interpretation. If you were using Promptfoo to run quick sanity checks on prompt quality rather than full test suites, PromptEval is the zero-friction replacement.

The Pro plan ($39/month) adds the Batch A/B Test wizard — two prompts, up to 7 evaluation criteria, up to 10 test inputs, results without writing a line of code. See the how to A/B test prompts systematically guide for the full method.

What it doesn't do: YAML-based assertion testing, CI/CD pipeline integration, red-teaming, or production trace monitoring. If those were your Promptfoo use cases, look further down this list.

2. DeepEval (Confident AI) — closest feature match for output testing

DeepEval is the most direct replacement for Promptfoo's output testing and CI/CD assertion workflow. It uses a Python SDK, supports custom metrics, and integrates with pytest — so existing test pipelines need minimal rewiring.

Where Promptfoo used YAML configs for defining assertions, DeepEval uses Python test cases with metric classes. The mental model transfers cleanly. The open-source core covers most of what Promptfoo's free tier offered; Confident AI's cloud layer adds dashboards, regression tracking, and the DeepTeam red-teaming module for adversarial testing.

Setup takes 20-30 minutes if you're comfortable with Python. If you had Promptfoo running in CI, DeepEval is the path of least resistance.

3. Braintrust — best for teams that need production monitoring

Braintrust occupies a different part of the evaluation space. It's less about catching prompt bugs in development and more about tracking model behavior in production — experiment logging, version comparison, and shared dashboards for teams.

It's YC-backed with a solid SDK and has been the default recommendation in a lot of "LLM observability" conversations since 2024. The comparison table at the top of most Promptfoo alternatives articles tends to push Braintrust hard. That's partly because Braintrust has a generous affiliate program, and partly because it genuinely is good for what it does.

If you had Promptfoo in CI for development testing and you want to extend evaluation into production monitoring, Braintrust is the logical next layer — not an either/or. See the full comparison of prompt evaluation tools for a fuller head-to-head.

4. LangSmith — best for LangChain/LangGraph teams

If your stack is LangChain or LangGraph, LangSmith is the obvious choice. It's built by the same team, traces are native, and the evaluation workflow fits how LangChain projects are structured. The developer tier is free up to a generous usage threshold.

For teams not on LangChain, LangSmith's tight integration becomes a liability — the SDK assumes LangChain primitives throughout. Switching away from LangChain while keeping LangSmith doesn't work well in practice.

5. Adaline — best for enterprise release governance

Adaline targets a narrower use case: approval workflows and compliance documentation for AI feature releases. Think regulated industries — finance, healthcare, legal — where prompts need sign-off before deployment and audit trails matter.

It's not a Promptfoo replacement in the technical testing sense. It's what sits on top of your testing layer to handle governance. If your Promptfoo use case was "make sure prompts pass a bar before shipping to production," Adaline handles the policy layer; DeepEval or PromptEval handles the technical evaluation layer. Setup is enterprise-contract territory.

6. Garak / Microsoft PyRIT — best for red-teaming and security

This is the use case OpenAI actually acquired Promptfoo for. And it's the one where the open-source alternatives are strongest.

Garak (NVIDIA-backed, open source) scans LLMs for vulnerabilities — prompt injection, jailbreaks, data leakage, harmful content generation. It runs as a CLI tool against any model with an API. Microsoft PyRIT does similar work with a Python orchestration layer designed for adversarial simulation at scale.

Both require more setup than Promptfoo's red-teaming module, but they go deeper on security-specific probes. If security testing was your primary Promptfoo use case, these are your tools — neither is going anywhere, and neither depends on OpenAI's roadmap decisions.

When Promptfoo is still the right answer

Honestly? If you have a working Promptfoo setup and you're not worried about long-term maintenance, there's no urgent reason to switch. The project is open source. Nothing breaks on March 10. Your YAML test configs run the same as they did in February.

The case for staying: Promptfoo's YAML-based assertion syntax is genuinely clean, the multi-provider comparison feature (running the same test against GPT-4o, Claude, Llama in one config) has no direct equivalent elsewhere, and the community-contributed plugins for specific vulnerability types are extensive.

The case for switching: you're building on a non-OpenAI stack and want a tool whose roadmap isn't steered by a competitor, you need features (production monitoring, structural scoring) that adjacent tools do better, or you want to reduce maintenance surface area before an issue surfaces in production.

Either answer is defensible. What's not defensible is treating this as a non-decision. The acquisition changed the maintenance equation. Make an active call.

FAQ

What happened to Promptfoo?
OpenAI acquired Promptfoo on March 9, 2026. The full announcement is at openai.com/index/openai-to-acquire-promptfoo. Promptfoo stays open source; the technology integrates into OpenAI's Frontier platform. Promptfoo had 25%+ Fortune 500 enterprise adoption at acquisition time, primarily for red-teaming and output testing.

Is there a free Promptfoo alternative?
Several. DeepEval and Garak are fully open source. PromptEval has a free plan with 3 evaluations/month — no credit card required. LangSmith has a developer tier. Braintrust has a free tier with usage limits.

Which alternative works without an API key or Python?
PromptEval is the only one on this list that runs entirely in a browser with no setup. You don't need an API key for structural scoring — just paste a prompt and go. The token optimizer also runs without authentication.

Does the acquisition affect Promptfoo's open-source license?
No. Promptfoo remains open source under its current license. OpenAI confirmed this in the acquisition announcement. What changes is who controls the roadmap and where engineering resources go — not the license terms on existing code.

Apply what you just learned — evaluate your prompt free.