AI assistants, chat and model tools
LLM gateways and model comparison
Tools for working across many LLMs: unified API routers with fallback and cost tracking, side-by-side model comparison and benchmarking, and local model runners with hardware fit checks, aimed at developers and power users juggling multiple models.
Built for: Developers building on LLM APIs
Projects since May 04
320
Different builders
308
Last 4 weeks vs 8 before
▲ +32%
AI is the core
55%
Projects per week
Mostly developer tool or library (37%), web app (22%), api or backend service (18%) · from r/SideProject, r/vibecoding, r/SaaS, r/IMadeThis
Latest
- Owl Lattice — Lets users work with multiple AI models and organize AI-assisted workflows in one desktop app.“[PAID] Test an experimental multi-AI desktop app and give feedback 20 for ~30 minutes (18+, Windows users)”
- TokenSaver Image Optimizer — Crops and resizes images attached to chat sites so they use fewer estimated tokens before upload.“One 4K screenshot can cost 3x more tokens than it needs to. Here's a free fix for Claude, ChatGPT & Cursor”
- CrowdGPT — Coordinates volunteers' own GPUs to collaboratively train an open-source large language model.“I got tired of big AI companies, so i created CrowdGPT.”
- Lison — Gives access to many third-party AI models for chat, images, video and music in one web interface.“I built Lison — one studio for 40+ AI models (chat, images, video, music)”
- BiNeuron — Runs AI models locally using Hugging Face model files.“I did a project to run AI models locally with Hugging Face.”
- TensorSharp — Runs large language models locally with an inference engine that offloads model weights across GPU VRAM, system RAM, and SSD using MoE-aware scheduling.“I built an open-source inference engine that runs a 176B MoE model on my RTX 3080 laptop”
- Runs local LLMs as a chat and document review assistant that analyzes PDFs, Office files, and images without sending data to the cloud.“Pricacy-first local AI interface for document reviews and chat”
- ObitMC — Serves Qwen language model inference through an OpenAI-compatible API by running on interruptible cloud compute.“Test my new LLM inference engine and get 100M free tokens and then 60% cheaper inference”
- Auker 1.0 — Splits a task into subproblems and learns how to allocate models, agents, tools, and reasoning across them to lower cost at similar accuracy.“We let our AI agent change how it allocates models—and cut its benchmark cost about 6×”
- AskAIR — Routes each question to the AI model judged best for that kind of question and shows the answer in-app.“I added up what it costs to subscribe to 8 AI tools separately, so I built one app that picks the right one for each question”
- Local LLM Finder — Recommends local LLMs that fit a user's chosen hardware and intended use, with memory and context estimates.“I built a tool for finding local LLMs that fit your hardware”
- Middleware — Uses user corrections to continuously retrain task-specific LoRA adapters and serves them through a drop-in API proxy.“We're building an API to keep task-specific models up to date”
- Routes OpenAI-compatible chat requests across several free LLM provider tiers, falling over to the next model when one hits its rate limit.“I kept hitting free-tier rate limits on my own scripts, so I built a router that stacks a few free providers behind one address”
- Teaches how language models work through an interactive guide that builds and trains a tiny LLM from scratch.“From zero to a tiny LLM: an interactive guide to how language models actually work”
- CogFoundry — Provides a single API that gives access to dozens of text, image, video, and audio AI models through one key.“We made CogFoundry — one API that keeps up with the flood of new AI models”
- AgentBill — Records per-customer LLM API usage and cost from OpenAI, Anthropic and Google calls and can block calls that would exceed a dollar budget.“Which of your customers is eating your OpenAI bill? I built a tool that tells you. Looking for 10 founders to try it.”
- MICA — Predicts the next bytes of text using a tiny byte-level language model built from integer rules instead of neural layers.“MICA - My 4.47 MB language model got better at predicting text, but still can't finish a sentence well”
- Jev Prime — Lets users chat with a text classifier model that has been trained to produce conversational replies.“i made Jev talk. paper and code below”
- Intercepts LLM API calls from AI agents, prunes their context before billing, and serves duplicate calls from a semantic cache.“We cut an AI agent's token consumption by 81% (and saved a startup $4k/mo) by intercepting the context layer.”
- doushi — Turns a prompt and a dataset into a hosted machine learning model via a web app and CLI.“Lovable, but for ML.”
Most discussed
- JEV — Answers yes-or-no questions from a small language model, letting users probe what the model knows.“Experiment to see if JEV is smart”
- Godwit — Runs large mixture-of-experts language models on small Apple Silicon Macs by streaming expert weights from SSD as needed.“I built an engine in Swift that runs a 120-billion-parameter AI model on a 16GB MacBook Air”
- Sends one question to multiple AI models at once and shows their answers side by side using users' own API keys.“Need advise your honest opinion”
- AI Wallet — Compares token prices across major AI models and recommends cheaper options for a given use case.“I built an iOS app because I couldn't figure out which AI API was actually cheapest for my app”
- Displays side-by-side SVG outputs from many AI models generated from the same prompt so they can be compared visually.“SVGs of a hamster playing table tennis”
- GPU Router — Routes LLM API requests across multiple discounted inference providers behind a single endpoint, choosing the cheapest provider for each request.“I built Openrouter, except you save 88% on GPT 6 Astra, 74% on Fable 5.1, 98% on GLM 5.3, and 400+ more models”
- Proxies OpenAI API calls and reports token cost grouped by customer, feature or model.“How do you know which customer is burning your OpenAI budget?”
- SmophyAI — Gives access to many AI models from one subscription-based workspace.“2 months after launching here: paying customers around the world, a billing system that was silently canceling them, and analytics that turned out to be 75% bots”
- AskAIR — Routes each question to the AI model judged best for that kind of question and shows the answer in-app.“I added up what it costs to subscribe to 8 AI tools separately, so I built one app that picks the right one for each question”
- Promptera AI — Stores LLM prompt blueprints with JSON output structuring and version control so prompts can be rolled back.“I posted my AI SaaS idea here yesterday. The feedback completely changed my roadmap. 🤯”