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LLM Playground OS
Local-first playground to test compare & version LLM prompts
🛠️ Open-source, local-first workbench to test, compare, and version LLM prompts across multiple providers—including OpenAI, Anthropic, Gemini, Groq, and Ollama. Key Features: • Compare outputs side-by-side in real time • Track prompt variations and system instructions • 100% privacy-focused: runs locally without middleman servers • Multi-model support for cloud and local models (Ollama) Designed for developers, prompt engineers, and creators building AI workflows.
I built LLM-Playground-OS to solve a friction point I kept running into daily while engineering AI workflows.
The Problem Testing prompts across different providers usually means jumping between multiple web tabs (ChatGPT, Claude, Gemini UI), copying API keys into SaaS tools with unclear privacy practices, or struggling to run side-by-side comparisons with local models like Ollama.
The Solution LLM-Playground-OS is a 100% open-source, local-first workbench designed to give developers total ownership of their prompt testing stack:
Local-First & Private: Your API keys and prompt history stay on your local machine—no proxy servers or subscriptions.
Side-by-Side Playground: Compare output quality, latency, and response variations in real time across OpenAI, Anthropic, Gemini, Groq, and Ollama.
Prompt Versioning & History: Organize, iteration-track, and refine system prompts efficiently.
What's Next? Since this is fully open-source, I'm actively expanding provider integrations and local testing tools. I’d love to hear your feedback, feature ideas, or any contributions on GitHub!
What does your current prompt testing setup look like?
About LLM Playground OS on Product Hunt
“Local-first playground to test compare & version LLM prompts”
LLM Playground OS was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #18 on the daily leaderboard. 🛠️ Open-source, local-first workbench to test, compare, and version LLM prompts across multiple providers—including OpenAI, Anthropic, Gemini, Groq, and Ollama. Key Features: • Compare outputs side-by-side in real time • Track prompt variations and system instructions • 100% privacy-focused: runs locally without middleman servers • Multi-model support for cloud and local models (Ollama) Designed for developers, prompt engineers, and creators building AI workflows.
On the analytics side, LLM Playground OS competes within GitHub — topics that collectively have 41.4k followers on Product Hunt. The dashboard above tracks how LLM Playground OS performed against the three products that launched closest to it on the same day.
Who hunted LLM Playground OS?
LLM Playground OS was hunted by Fidel Alejandro Fernandez Arias. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of LLM Playground OS including community comment highlights and product details, visit the product overview.
Fidel Alejandro Fernandez Arias
Hey Product Hunt community! đź‘‹
I built LLM-Playground-OS to solve a friction point I kept running into daily while engineering AI workflows.
The Problem
Testing prompts across different providers usually means jumping between multiple web tabs (ChatGPT, Claude, Gemini UI), copying API keys into SaaS tools with unclear privacy practices, or struggling to run side-by-side comparisons with local models like Ollama.
The Solution
LLM-Playground-OS is a 100% open-source, local-first workbench designed to give developers total ownership of their prompt testing stack:
Local-First & Private: Your API keys and prompt history stay on your local machine—no proxy servers or subscriptions.
Side-by-Side Playground: Compare output quality, latency, and response variations in real time across OpenAI, Anthropic, Gemini, Groq, and Ollama.
Prompt Versioning & History: Organize, iteration-track, and refine system prompts efficiently.
What's Next?
Since this is fully open-source, I'm actively expanding provider integrations and local testing tools. I’d love to hear your feedback, feature ideas, or any contributions on GitHub!
What does your current prompt testing setup look like?