Alternatives
Products that do what Epoch does
A generative interactive interface for LLMs
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I built LocalGPT over 4 nights as a Rust reimagining of the OpenClaw assistant pattern (markdown-based persistent memory, autonomous heartbeat tasks, skills system). It compiles to a single ~27MB binary — no Node.js, Docker, or Python required. Key features: - Persistent memory via markdown files (MEMORY, HEARTBEAT, SOUL markdown files) — compatible with OpenClaw's format - Full-text search (SQLite FTS5) + semantic search (local embeddings, no API key needed) - Autonomous heartbeat runner that checks tasks on a configurable interval - CLI + web interface + desktop GUI - Multi-provider:…
Feb 2026 · github.com
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Hi HN A few folks and I have been working on this project for a couple weeks now. After previously working on the Docker project for a number of years (both on the container runtime and image registry side), the recent rise in open source language models made us think something similar needed to exist for large language models too. While not exactly the same as running linux containers, running LLMs shares quite a few of the same challenges. There are "base layers" (e.g. models like Llama 2), specific configuration to run correctly (parameters, temperature, context window sizes etc). There's…
2023 · github.com
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Hey, Jared Palmer (creator of this playground) here. Really excited to ship this. I’ve been building this over the past few weeks to compare LLMs from different providers like OpenAI, Anthropic, Cohere, etc. At Vercel, I manage our Frameworks division (including Next.js, Svelte, and Turbo) and wanted to also dogfood some of the latest features in a slightly larger application. This playground takes a lot of inspiration from https://nat.dev and is built on Tailwind, ui.shadcn.com, and some upcoming Vercel products we’re announcing soon. We’re going to continue adding models to…
2023 · play.vercel.ai
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One of the most frequent questions one faces while running LLMs locally is: I have xx RAM and yy GPU, Can I run zz LLM model ? I have vibe coded a simple application to help you with just that. Update: A lot of great feedback for me to improve the app. Thank you all.
2025 · can-i-run-this-llm-blue.vercel.app
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Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2024 · github.com
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Demo starts at 50m into the video. This was a bit terrifying to record because 2am the previous night everything was totally broken after a major refactor (so that we could add external LLM support as well as local GPUs). But pressure can be a useful force :-D We start with a stack deployed on my laptop without a GPU, pointing to together.ai so we can run open source LLMs easily without having to have access to a GPU. We show simple inference through the ChatGPT-like web interface (with users, sessions etc) and then simple drag'n'drop RAG. Then we show some helix apps defined as yaml: Marvin…
2024 · youtube.com
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Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…
2023 · gethorizon.ai
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Hey everyone, I’ve been working on a project called L88 — a local RAG system that I initially focused on UI/UX for, so the retrieval and model architecture still need proper refinement. Repo: https://github.com/Hundred-Trillion/L88-Full I’m running this on 8GB VRAM and a strong CPU (128GB RAM). Embeddings and preprocessing run on CPU, and the main model runs on GPU. One limitation I ran into is that my evaluator and generator LLM ended up being the same model due to compute constraints, which defeats the purpose of evaluation. I’d really appreciate feedback on:…
Feb 2026
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Built a simple web app that tells you which open-source LLMs will work on your hardware. It auto-detects your specs, shows compatible models from Hugging Face, gives realistic performance estimates (tokens/sec), and recommends quantization settings. You can also manually input specs to see "what if I upgraded my RAM?" Made this after wasting time downloading giant models only to find they crawled on my hardware. Hope it saves you some frustration!
2025 · caniusellm.com
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Hey HN! Over the past few weeks, I’ve been working on DataBridge, an open-source solution for data ingestion and querying across text, PDFs, images, and videos. In our latest update, we’ve added a fully local deployment option: - No internet required – Runs entirely offline. - Customizable Models – Supports any LLM and embedding model via Ollama (with options for any other private providers) - Extensibility – You can plug in your own models or tools easily. This local-first approach ensures better privacy, security, and flexibility, especially for teams dealing with sensitive data. You can…
2025 · github.com
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Hi HN, we're Ashpreet, Eli and Yash and we're excited to share Phidata: a collection of AI Apps built with open-source tools. While helping teams build AI products, we built templates for spinning up LLM Apps quickly. Today we're open-sourcing our templates for building: - RAG LLM Apps - Autonomous LLM Apps - Multimodal LLM Apps - Data Engineering LLM Apps Templates are built with FastApi for serving, Streamlit for prototyping, PgVector for vectors and PosgreSQL for storage. Run them locally using docker and in production on AWS - with 1 command. - Github:…
2023 · github.com
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Hi HN, I built OpenGraviton, an open-source AI inference engine that pushes the limits of running extremely large LLMs on consumer hardware. By combining 1.58-bit ternary quantization, dynamic sparsity with Top-K pruning and MoE routing, and mmap-based layer streaming, OpenGraviton can run models far larger than your system RAM—even on a Mac Mini. Early benchmarks: TinyLlama-1.1B drops from ~2GB (FP16) to ~0.24GB with ternary quantization. At 140B scale, models that normally require ~280GB fit within ~35GB packed. Optimized for Apple Silicon with Metal + C++ tensor unpacking, plus…
Mar 2026 · github.com
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Hi all, I threw together a small prototype I am calling “Notepad.ai”. A new take on UIs for interacting with LLMs. While I enjoy using LLM’s in the chat format I wanted to see what it would be like to do it in a more long form style. It let’s you write in a pretty free form, much like Window’s Notepad, but you can choose to hit ctrl+[ to analyze the text with a preset prompt of your choosing. It has a few other small features. It’s WIP and very experimental. I would appreciate any feedback or thoughts. Video: https://youtu.be/ntdlgFmSxQY Live Demo:…
2024 · github.com
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I built localLLLM: a small community project for running local models. Live: https://locallllm.fly.dev The goal is simple: if someone has model + OS + GPU + RAM, they should get steps that actually work (ideally one liner) I need help populating and validating guides. If you run local models, please submit one working recipe (or report what failed). Would love to hear general feedback as well!
Apr 2026 · locallllm.fly.dev
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