Updated May 21, 2026 · ~6 min read · Honest comparison, not a takedown
The 30-second answer. Promptfoo is an open-source LLM evaluation framework built for engineers who want to run systematic, reproducible prompt tests in CI/CD pipelines — complete with YAML-driven test configs, red-teaming, regression checks, and a local dashboard. TinyTools' Prompt Injection Tester and LLM Prompt Optimizer are free, no-install browser tools: paste a prompt, get instant feedback on injection vulnerabilities or quality issues, and move on. If you're shipping an AI product and need automated evaluation across hundreds of test cases in your CI pipeline, Promptfoo is purpose-built for that. If you need a fast sanity check on a single prompt without installing anything, TinyTools is faster to reach.
What each one actually is
Promptfoo is an open-source command-line tool and evaluation framework released in 2023 that has become one of the most popular options for LLM testing among developers. At its core it lets you define prompts, providers (OpenAI, Anthropic, Ollama, any API), and a set of expected outputs or assertion criteria in a YAML config file, then run all combinations and grade the results. The output is a local web dashboard showing pass/fail rates, regressions versus previous runs, and side-by-side provider comparisons. Promptfoo also ships a red-teaming module that automatically generates adversarial prompts to probe for jailbreaks, data leakage, and prompt injection. It is free and self-hosted; a cloud tier called Promptfoo Cloud adds team collaboration, hosted dashboards, and persistent eval history for $0–$300+/month depending on volume.
TinyTools' browser prompt tools are a suite of lightweight, no-install utilities aimed at the moment before you commit to a framework. The Prompt Injection Tester takes a system prompt and a simulated user message and flags injection-risk patterns, boundary violations, and jailbreak vectors with an explanation of what went wrong and why. The LLM Prompt Optimizer scores a prompt for clarity, specificity, and likely output quality, then suggests rewrites. The Prompt Grade tool assigns a letter grade to any prompt with a rubric. None require an account, API key, or local installation — they run in your browser tab and forget you the moment you close it.
Side-by-side feature comparison
Feature
TinyTools
Promptfoo
Price (core tool)
Free, forever
Free (OSS), self-hosted
Installation required
None — runs in browser
npm / npx required
Account / signup required
No
No for OSS; required for Cloud tier
Prompt injection detection
Yes — browser, instant
Yes — via red-team module
Automated multi-case evaluation
One prompt at a time
Yes — hundreds of test cases
CI/CD pipeline integration
No
Yes — GitHub Actions, etc.
Multi-provider comparison (OpenAI vs Anthropic vs …)
No
Yes — core feature
YAML / config-driven test suites
No
Yes
Regression testing (diff against baseline)
No
Yes
Red-teaming / adversarial prompt generation
Manual injection patterns
Automated red-team module
Prompt quality scoring & rewrites
Yes — Optimizer & Grade tools
Via custom assertions
Local web dashboard
Browser tab only
Yes — localhost UI
Team collaboration (shared evals)
No
Promptfoo Cloud (paid)
Data stays on your machine
Yes (in-browser)
Yes for OSS; cloud tier sends data
Works without an LLM API key
Yes
Requires provider API keys
Mobile-friendly
Yes
CLI — not applicable
Pricing comparison
Promptfoo OSS is free to self-host with no usage limits — you only pay for the LLM API calls you make to your chosen provider. The cloud tier adds hosted dashboards, team sharing, and managed infra:
Plan
TinyTools
Promptfoo (2026)
Free
Unlimited, no signup, no ads
OSS self-hosted — unlimited evals, no dashboard hosting
Entry paid
n/a
Promptfoo Cloud Starter: ~$0–free tier with limits
Team tier
n/a
~$99–$300+/mo — hosted dashboard, team seats, SSO
LLM API costs
None — no API calls made
Pass-through — you pay your provider (OpenAI, Anthropic, etc.)
Enterprise
n/a
Custom pricing — on-prem deploy, SLA, audit logs
For individual developers, Promptfoo OSS is genuinely free and the only real cost is your time setting it up and the LLM API tokens you spend on test runs. TinyTools is free with zero setup and zero API cost, but it doesn't run automated evals.
A note on what "prompt testing" means
These two tools address different parts of the prompt-testing problem. Promptfoo is about systematic evaluation at scale: does my prompt reliably produce the right format across 200 edge-case inputs? Does it regress when I change the model version? TinyTools is about instant qualitative feedback: is this prompt vulnerable to injection? Is it well-written? The honest answer is that a serious AI product team eventually needs both — a quick-check tool for the authoring loop and a framework tool for CI/CD validation.
When Promptfoo is the better choice
Promptfoo has earned real adoption among AI engineers, and there are situations where it's clearly the right pick. Use it when:
You're building an AI product and need regression safety. Every time you update your system prompt or switch models, you want to know if outputs changed. Promptfoo's baseline comparison catches regressions that a quick manual check would miss.
You want to compare models before committing to one. Promptfoo's multi-provider setup lets you run the same test suite against GPT-4o, Claude 3.7, Gemini, and a local Ollama model simultaneously and see a side-by-side score table.
You need automated red-teaming. Promptfoo's red-team module generates hundreds of adversarial variants automatically — far more coverage than manually pasting prompts into a browser tool one by one.
CI/CD is a requirement. If a PR that changes a prompt should fail a GitHub Actions check, Promptfoo is the standard way to wire that up. TinyTools has no CLI or API.
Your team needs to share eval results. Promptfoo Cloud's hosted dashboard lets non-engineers on your team view results without touching the terminal. TinyTools is entirely solo and stateless.
When TinyTools is the better choice
The honest case for TinyTools is narrower but genuine:
You need an answer in 10 seconds, not 10 minutes. Installing Promptfoo, writing a YAML config, adding your API key, and running npx promptfoo eval is a real task. For a one-off check on a prompt you're about to paste into ChatGPT, the browser tool is faster by a large margin.
You don't have an API key or don't want to spend tokens. TinyTools' injection tester and optimizer analyze the prompt text itself — no LLM calls are made, no API key is consumed. Promptfoo requires a live provider to generate and score outputs.
You're a non-developer checking prompt quality. A content writer, marketer, or product manager can use TinyTools without touching a terminal. Promptfoo's primary interface is a CLI that assumes comfort with Node and config files.
You're writing a prompt for the first time and want to learn. The Prompt Grade tool and LLM Prompt Optimizer explain why a prompt is weak and suggest rewrites — useful for learning, not just scoring. Promptfoo scores outputs against your own assertions, which assumes you already know what good output looks like.
Privacy matters for the prompt content. TinyTools runs in your browser — your prompt text never leaves your machine. The Promptfoo OSS self-hosted path also keeps data local, but if you use the cloud tier, evals are processed on Promptfoo's infrastructure.
Three concrete use cases
1. A startup founder iterating on their chatbot's system prompt
You've rewritten your system prompt six times and keep getting off-topic responses. Recommendation: Start with TinyTools' Prompt Injection Tester and LLM Prompt Optimizer to catch structural issues quickly without burning API credits. Once you have a solid draft, set up Promptfoo to run 50 representative user inputs against it to measure consistency — that's where the framework pays off.
2. A solo developer building an internal AI tool
You want to make sure your prompt doesn't leak sensitive instructions when users get creative. Recommendation: TinyTools for a quick injection scan during development, Promptfoo's red-team module before you ship. They complement each other well — the browser tool is fast in the authoring loop, the CLI is thorough in the validation step.
3. An AI team at a company with 10+ engineers
You need prompt evals to block bad PRs, track model performance over time, and let PMs view results without running CLI commands. Recommendation: Promptfoo. The OSS version handles the CI/CD integration, and Promptfoo Cloud handles the sharing layer. TinyTools doesn't have team features or CI hooks, and that's fine — it's not trying to be an evaluation platform.
Switching costs and lock-in
Promptfoo OSS stores evals in local files (JSON) that are portable — if you stop using it, you keep your test configs. Promptfoo Cloud adds lock-in through hosted history and dashboards; canceling means losing that. TinyTools has zero lock-in by design: no account, no history, nothing to migrate. The two tools are also not mutually exclusive — many developers use browser tools like TinyTools for quick checks during authoring and a framework like Promptfoo for systematic CI validation.
Verdict
Promptfoo and TinyTools are tools for different moments in the prompt-development lifecycle. Promptfoo is an evaluation framework: systematic, configurable, CI-friendly, and designed for engineers who take prompt quality seriously enough to treat it like software testing. If you're building an AI product, you should probably know what Promptfoo is and have it set up at some point.
TinyTools is for the moment before you're ready for a framework — or the moment where a framework is overkill. Paste a prompt, get a read on it, and move on. No API key, no npm, no YAML. For quick checks on injection risk, prompt structure, or prompt quality, TinyTools is the fastest path from "I wrote this prompt" to "I know what's wrong with it."