A/B testing LLM silence with one system-prompt toggle
Twitter experiment about LLM silence with no actual tool or usable product.

One prompt, many models — that simple idea is executed with practical extras: independent conversation threads per model, full-text history/search, and bring‑your‑own API keys so you don't copy/paste. The landing page sells the daily‑driver vibe (lifetime one-time pricing is an attention grabber), but the concept itself is not novel; I'd want clearer UI for cost controls, API key security and model/version management before trusting it for heavy use.
Prompt engineers, AI hobbyists, product people and developers who compare outputs across multiple LLMs
I was writing a prompt, then end up pasting it into multiple LLMs to compare responses.
So I built an app that does that for you, send a single prompt to multiple LLM models and get responses side by side
It is a tool for anyone who wants to compare outputs across different LLM models and quickly see results of all LLM models.
Why use one AI model when you can use all of them in single interface!
Features: - Parallel Responses — Query multiple LLMs at once and compare results in real time. - Pin, Search & History — Easily organize, find and revisit your conversations. - Access All LLMs in One Place — GPT, Claude, Gemini and more incoming! - Bring your own API keys: add keys from each provider’s developer portal inside the app. - Share your chats with others
I built this tool for my personal use first and I am using it daily now.
Feedbacks are appreciated!
Product Link: MultiLLM.pro
Happy Prompt-maxxing!
Twitter experiment about LLM silence with no actual tool or usable product.
Orchestrates real-time skepticism between models to catch hallucinations before you see them.
API wrapper for Claude and GPT with rate-limiting tiers; existing solutions (OpenRouter, LiteLLM) already do this.
Multi-vendor token comparison with specific cut recommendations and dollar savings at scale.
Tackles persona collapse with architecture, but lacks proof-of-concept or working implementation.
Local prompt optimization framework for any Windows app, but learning mode lacks substance.