AI · alternatives · 2026
24 alternatives to Live Demo of GraphRAG with GPT-4o mini
Hi HN, Microsoft recently open-sourced the GraphRAG framework, which enables more contextual responses than traditional vector-based RAG, especially for summarization-focused queries on textual data. However, a common critique is the LLM costs for constructing the knowledge graph. With the newly released GPT-4o mini, working with GraphRAG would now be ~30x cheaper. We built a demo with quarterly earning call transcripts from a few S&P 100 companies comparing GraphRAG with GPT-4o, GraphRAG with GPT-4o mini, and Baseline RAG. Try out the demo here: https://graphrag-demo.deepset.ai…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Live Demo of GraphRAG with GPT-4o mini launched in 2024; newer entries below may have overtaken it.
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Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
2024 · github.com · its alternatives →
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Fast and efficient models optimized for coding and subagents
Mar 2026 · openai.com · its alternatives →
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Announcing GPT-4.1, GPT-4.1 mini, & GPT-4.1 nano in the API
2025 · openai.com · its alternatives →
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- 5IB
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
2025 · blog.kuzudb.com · its alternatives →
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TensorZero▲307Hi 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:…
2025 · github.com · its alternatives →
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Hi HN, I have been working with regulation-heavy documents lately, and one thing kept bothering me. Flat RAG pipelines often fail to retrieve related articles together, even when they are clearly connected through references, definitions, or clauses. After trying several RAG setups, I subjectively felt that GraphRAG was a better mental model for this kind of data. The Microsoft GraphRAG paper and reference implementation were helpful starting points. However, in practice, I found one recurring friction point: graph storage and vector indexing are usually handled by separate systems, which…
Jan 2026 · github.com · its alternatives →
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LLM Stats▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
Oct 2025 · llm-stats.com · its alternatives →
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I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
2024 · embedding.io · its alternatives →
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Hey HN! We’ve forked Jupyter Lab and added AI code generation features that feel native and have all the context about your notebook. You can see a demo video (2 min) here: https://www.tella.tv/video/clxt7ei4v00rr09i5gt1laop6/view Try a hosted version here: https://pretzelai.app Jupyter is by far the most used Data Science tool. Despite its popularity, it still lacks good code-generation extensions. The flagship AI extension jupyter-ai lags far behind in features and UX compared to modern AI code generation and understanding tools (like…
2024 · github.com · its alternatives →
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TL;DR: Vector-based RAG performs poorly for many real-world applications like codebase chats, and you should consider 'language maps'. Part of our mission at Mutable.ai is to make it much easier for developers to build and understand software. One of the natural ways to do this is to create a codebase chat, that answer questions about your repo and help you build features. It might seem simple to plug in your codebase into a state-of-the-art LLM, but LLMs have two limitations that make human-level assistance with code difficult: 1. They currently have context windows that are too small to…
2024 · twitter.com · its alternatives →
- 12WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat · its alternatives →
- 13IG
Data automation and visualization platform for spreadsheet users.
2024 · columns.ai · its alternatives →
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I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
2023 · github.com · its alternatives →
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Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade RAG systems. Just a quick reminder: RAG helps Large Language Models (LLMs) use current information and specific knowledge. For example, it allows a programming assistant to use your latest documents to answer questions. The idea is to gather all the relevant information…
2024 · github.com · its alternatives →
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Hey HN! We're Paul, Preston, and Daniel from Zep. We've just open-sourced Graphiti, a Python library for building temporal Knowledge Graphs using LLMs. Graphiti helps you create and query graphs that evolve over time. Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is its ability to build a knowledge graph while handling changing relationships and maintaining historical context. At Zep, we build a memory layer for LLM applications. Developers use Zep to recall relevant user information from past conversations without including the entire…
2024 · github.com · its alternatives →
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Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com · its alternatives →
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Hey HN, I’m Zach from Superpowered AI (YC S22). We’ve been working in the RAG space for a little over a year now, and we’ve recently decided to open-source all of our core retrieval tech. spRAG is a retrieval system that’s designed to handle complex real-world queries over dense text, like legal documents and financial reports. As far as we know, it produces the most accurate and reliable results of any RAG system for these kinds of tasks. For example, on FinanceBench, which is an especially challenging open-book financial question answering benchmark, spRAG gets 83% of questions correct,…
2024 · github.com · its alternatives →
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Hey hacker news, we launched a few weeks ago as a GPT-powered chatbot for developer docs, and quickly realized that the value of what we’re doing isn’t the chatbot itself. Rather, it’s the time we save developers by automating the extraction of data from their SaaS tools (Github, Zendesk, Salesforce, etc) and helping transform it to contextually relevant chunks that fit into GPT’s context window. A lot of companies are building prototypes with GPT right now and they’re all using some combination of Langchain/Llama Index + Weaviate/Pinecone + GPT3.5/GPT4 as their stack for…
2023 · github.com · its alternatives →
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Hey HN, exciting news! Our RAG framework, Cognita (https://github.com/truefoundry/cognita), born from collaborations with diverse enterprises, is now open-source. Currently, it offers seamless integrations with Qdrant and SingleStore. In recent weeks, numerous engineers have explored Cognita, providing invaluable insights and feedback. We deeply appreciate your input and encourage ongoing dialogue (share your thoughts in the comments – let's keep this ‘open source’). While RAG is undoubtedly powerful, the process of building a functional application with it can feel…
2024 · github.com · its alternatives →
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I made a simple GraphRAG call nano-graphrag. The reason is I try to hack the official implementation released by Microsoft but that version is very hard to read/hack. This algorithm should not be implemented that annoying, I think. So I made a simpler one. It's about 800-900 lines of Python, and it's portable.
2024 · github.com · its alternatives →
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IgnitionRAG▲83Multimodal RAG platform, from POC to production in minutes
Apr 2026 · ignitionrag.com · its alternatives →
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Hey HN fam, We’ve seen developers spend a lot of time implementing advanced RAG techniques from scratch. While these techniques are essential for improving performance, their implementation requires a lot of effort and testing! To help with this process, our team (Athina AI) has released Open-Source Advanced RAG Cookbooks. This is a collection of ready-to-run Google Colab notebooks featuring the most commonly implemented techniques. Please show us some love by starring the repo if you find this useful!
2024 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →