AI · alternatives · 2026
24 alternatives to "Be horse." – a diffusion language model on an M2 Air
Try the demo here: https://llm-trajectory.boesch.dev/ This is a write-up of a system I designed at a previous job. It's a natural language interface for industrial robots. The demo runs MuJoCo in the browser via WASM. The demo uses a free-tier LLM API with rate limiting, so it might be slow or unavailable under load, but feel free to check out the code and hook up your own inference service: https://github.com/Encrux/llm_trajectory
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com · its alternatives →
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Dream 7B▲191Powerful Open Diffusion LLM, Beyond Autoregressive
2025 · hkunlp.github.io · its alternatives →
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I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.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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Build your own high performance LLM inference engine in C++ and CUDA - a smaller version of vLLM - jmaczan/tiny-vllm
May 2026 · github.com · its alternatives →
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G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
- 8IB
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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Hi everyone, I'm happy to announce the release of Kalosm! [Kalosm](https://floneum.com/kalosm/) is a framework for embedded AI in rust. ## What is Kalosm? Kalosm provides a simple interface for pre-trained language, audio, and image models models. To make it easy to use with these models in your application, Kalosm includes a set of integrations other systems like your database or documents. ```rust use kalosm::language::*; #[tokio::main] async fn main() { let mut model = Llama::new_chat(); let mut chat = Chat::builder(&mut model) .with_system_prompt("The assistant will…
2024 · floneum.com · its alternatives →
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DIMBA II: a 288M-parameter masked-diffusion language model on a bidirectional Mamba-2 backbone. What worked, what failed, and what we
Jul 2026 · hamiltonianresearch.xyz · its alternatives →
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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 · its alternatives →
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I trained the 65b model on my texts so I can talk to myself. It's pretty useless as an assistant, and will only do stuff you convince it to, but I guess it's technically uncensored? I'll leave it up for a bit if you want to chat with it. I posted this to Reddit and had several hundred people talking to it. Salient points from that discussion: LLAMA 1 65b Rank 128 5 epochs Batch size 1, 256 cutoff Trained in the Oobabooga suite using bitsandbytes 4-bit quantization for the lora Loss around 1.5 seems to give the most coherent results Trained on raw text dumps that is then parsed by a crappy…
2023 · airic.serveo.net · its alternatives →
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Hi HN - Marcello and Vaibhav here. We built smolmodels to experiment with using LLMs for ML development. It's a fully open-source library that generates complete model training and inference code from natural language descriptions. It combines graph search with LLM code generation to find a model that gives as good predictions as possible. The core idea is that LLMs are overkill for a lot of predictive tasks. Smolmodels automates the trial-and-error process of finding the right model architecture and training approach, letting you build small, specialised models. You can either provide your…
2025 · github.com · its alternatives →
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My implementation of Thorsten Bell's book (Writing an Interpreter in Go) - actuallyachraf/monkey-giggle
2020 · github.com · its alternatives →
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It’s written in Python and I call it GoalChain. It lets you build a conversation flow graph that the user traverses. When there’s enough input it spits out a dictionary with the defined fields. Otherwise it will jump state to state as led by the user. It was fun to write, and it’s surprisingly effective if you keep in mind you’re prompt-engineering every string and field name. README.md has a mini-tutorial. Would be cool to get some ideas for how to build it further and what improvements I could make.
2024 · github.com · its alternatives →
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An educational Rust project for exporting and running inference on Qwen3 LLM family - reinterpretcat/qwen3-rs
2025 · github.com · its alternatives →
- 18IB
I’ve been playing around with local LLMs for the past couple of months and decided to build something that can run on an iPhone. It’s a universal app built with SwiftUI and the excellent ggml library. The model is an SFT fine tuned and 4 bit quantised version of the RedPajama-INCITE-Chat-3B-v1 OSS LLM. It works reasonably well on recent-ish (~3 year old) iPhones, iPads and Macs. It was launched on the App Store yesterday[1] and Product Hunt today[2]. It seems to be reasonably ok at natural language interactions, but given its size, does pretty badly at coding and reasoning. Also, it…
2023 · its alternatives →
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2023 · github.com · its alternatives →
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Hi HN, I'm thrilled to share with you think, a command-line tool that I developed while diving back into the programming scene. For the past few years, my focus had shifted from hands-on programming to managerial roles, my last one being at Affirm (I started Affirm's Polish office). However, I recently left my job to revisit my passion for coding and see if I could still write code that works. Not to mention that with what is currently going on in AI if you are a developer this probably the best possible time for a sabbatical in human history :) My first attempt was with LangChain, but I…
2023 · github.com · its alternatives →
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Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based BERT model with an LLM at work, and I realized it would be cool if I could do that instantly(especially since it was a prototype). At the time, I was considering a platform that could essentially help you train deep learning models without any code. It was my observation that much…
2024 · github.com · its alternatives →
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Hi HN! We (Thomas and Stéphan, hello!) recently released Model2Vec, a Python library for distilling any sentence transformer into a small set of static embeddings. This makes inference with such a model up to 500x faster, and reduces model size by a factor of 15 (7.5M params or 15/30MB on disk, depending on whether you use float16 or float32). This allows you to embed 50-100k documents per second on a cpu on a macbook. This reduction of course comes at a cost: distilled models are worse than their parent models. Even so, they are actually a lot better than large sets of conventional…
2024 · github.com · its alternatives →
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Hey Hacker News! We are excited to share our open-source project, KTransformers, a flexible framework designed for cutting-edge LLM inference optimizations! Leveraging state-of-the-art kernels from llamafile and marlin, KTransformers seamlessly enhances the performance of HuggingFace Transformers, making it possible to operate large 236B MoE models or extremely long 1M context locally with promising speed. KTransformers is a Python-centric framework designed with extensibility at its core. By implementing and injecting an optimized module with a single line of code, users gain access to a…
2024 · github.com · its alternatives →
- 24LI
2018 · languagemodels.io · 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 →