AI · alternatives · 2026

24 alternatives to GPT Circuits – Mapping the inner workings of simple LLMs

I've built an app that extracts interpretable 'circuits' from models using the GPT-2 architecture. These circuits reveal how specific inputs influence the probabilities of the next token in a sequence. While some tutorials present theoretical examples of how feedforward layers and attention heads may produce predictions, this app provides concrete examples of how information flows through an LLM. You can see, for example, the formation of features that search for simple grammatical patterns and trace their construction back to the use of more primitive features. Feel free to reach out with…

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. GPT Circuits – Mapping the inner workings of simple LLMs launched in 2024; newer entries below may have overtaken it.

1
Fully client-side GPT2 prediction visualizer▲153
Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…
2023 · perplexity.vercel.app · its alternatives →
2
I built a tiny LLM to demystify how language models work▲915
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 →
3
GPT-4.1 in the API▲375
Announcing GPT-4.1, GPT-4.1 mini, & GPT-4.1 nano in the API
2025 · openai.com · its alternatives →
4VI
Visual intuitive explanations of LLM concepts (LLM University)▲303
Hi HN, We've just published a lot of original, visual, and intuitive explanations of concepts to introduce people to large language models. It's available for free with no sign-up needed and it includes text articles, some video explanations, and code examples/notebooks as well. And we're available to answer your questions in a dedicated Discord channel. You can find it here: https://llm.university/ Having written https://jalammar.github.io/illustrated-transformer/, I've been thinking about these topics and how best to communicate them for half a…
2023 · its alternatives →
5MI
Microgpt is a GPT you can visualize in the browser▲282
very much inspired by karpathy's microgpt of the same name. it's (by default) a 4000 param GPT/LLM/NN that learns to generate names. this is sorta an educational tool in that you can visualize the activations as they pass through the network, and click on things to get an explanation of them.
Feb 2026 · microgpt.boratto.ca · its alternatives →
6
GPT‑5.4 mini and nano▲267
Fast and efficient models optimized for coding and subagents
Mar 2026 · openai.com · its alternatives →
7
LLM Explorer▲152
Find your best LLM for a local inference
2023 · its alternatives →
8
YourGPT 2.0▲215
Today we are launching YourGPT 2.0, an update focused on making support, sales, and operational workflows work together more smoothly in one system. This release improves how workflows are built, how the platform connects to external tools, and how context is maintained across long, multi-channel interactions. AI Studio now makes it much easier to create and refine workflows. You can describe the process you want in natural language and the system generates the full workflow for you. It can also help debug issues by showing what happened at each step and explaining where things went off…
Nov 2025 · yourgpt.ai · its alternatives →
9KG
Knowledge graph of restaurants and chefs, built using LLMs▲201
Hi HN! My latest side project is knowledge graph that maps the French culinary network using data extracted from restaurant reviews from LeFooding.com. The project uses LLMs to extract structured information from unstructured text. Some technical aspects you may be interested in: - Used structured generation to reliably parse unstructured text into a consistent schema - Tested multiple models (Mistral-7B-v0.3, Llama3.2-3B, gpt4o-mini) for information extraction - Created an interactive visualization using gephi-lite and Retina (WebGL) - Built (with Claude) a simple Flask web app to clean and…
2025 · theophilecantelob.re · its alternatives →
10IG
Interactive Graph by LLM (GPT-4o)▲45
Data automation and visualization platform for spreadsheet users.
2024 · columns.ai · its alternatives →
11
DB-GPT, an LLM tool for database▲156
open-source agentic AI data assistant for the next generation of AI + Data products. - eosphoros-ai/DB-GPT
2023 · github.com · its alternatives →
12
Bindly▲76
Hi HN, I’m a product designer by background, not a traditional software engineer. Over the last year, tools like Claude and ChatGPT completely changed how I work. I started with small internal tools, and now I’m “vibe coding” multiple highly personalized apps. As I iterated between Claude Code (implementation) and ChatGPT (ideation / thinking), I kept running into the same problem. To think clearly, I had to repeatedly re-explain: - what the code currently does, - what changed recently, - and why certain decisions were made. That re-summarization step became a real bottleneck. So I…
2016 · bind.ly · its alternatives →
13
Next-token prediction in JavaScript▲88
What inspired this project today was watching this amazing video by 3Blue1Brown called "But what is a GPT?" on Youtube (https://www.youtube.com/watch?v=wjZofJX0v4M - I highly recommend watching it). I added it to the repo for reference. When it clicked in my head that "knowing a fact" is nearly synonymous with predicting a word (or series of words), I wanted to put it to the test, because it seemed so simple. I chose JavaScript because I can exploit the way it structures objects to aid in the modeling of language. For example: "I want to be at the beach", "I will do it later",…
2024 · github.com · its alternatives →
14
Interactive 3D and 2D Visualization of GPT-2▲12
I’ve been building an interactive 3D + 2D visualization of GPT-2. It displays real activations and attention scores extracted from GPT-2 Small (124M) during a forward pass. The goal is to make it easier to learn how LLMs work by showing what is happening inside the model. The 3D part is built with Three.js, and the 2D part is built with plain HTML/CSS/JS. Would love to hear your thoughts or feedback!
Mar 2026 · llm-visualized.com · its alternatives →
15
dreamGPT: What if LLM hallucinations were a feature and not a bug?▲34
The first GPT-based solution that uses hallucinations from LLMs for divergent thinking to generate new and novel ideas. Hallucinations are often seen as a negative thing, but what if they could be used for our advantage? dreamGPT is here to show you how. The goal of dreamGPT is to explore as many possibilities as possible, as opposed to most other GPT-based solutions which are focused on solving specific problems.
2023 · github.com · its alternatives →
16AV
A Visual and Interactive Guide to the Basics of Neural Networks▲63
Discussions: Hacker News (63 points, 8 comments), Reddit r/programming (312 points, 37 comments) Translations: Arabic, French, Spanish Update: Part 2 is now live: A Visual And Interactive Look at Basic Neural Network Math Motivation I’m not a machine learning expert. I’m a software engineer by train
2016 · jalammar.github.io · its alternatives →
17
ThinkGPT: a library to prompt GPT to think, memorize and self-refine▲48
Agent techniques to augment your LLM and push it beyong its limits - jina-ai/thinkgpt
2023 · github.com · its alternatives →
18LT
Learning to (Learn at Test Time)▲13
I’m excited to share a project I’ve been working on for over a year, which I believe will fundamentally change our approach to language models. We’ve designed a new architecture, which replaces the hidden state of an RNN with a machine learning model. This model compresses context through actual gradient descent on input tokens. We call our method “Test-Time-Training layers.” TTT layers directly replace attention, and unlock linear complexity architectures with expressive memory, allowing us to train LLMs with millions (someday billions) of tokens in context. Our instantiations, TTT-Linear…
2024 · its alternatives →
19
LLM, a Rust Crate/CLI for CPU Inference of LLMs (LLaMA, GPT-NeoX, etc.)▲45
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 →
20
Symbolic Circuit Distillation: prove program to LLM circuit equivalence▲16
Hi HN, I've been exploring various applications of formal methods to ML/interpretability and I've been hoping to get more eyes on the approach. I have been working on a small interpretability project I call Symbolic Circuit Distillation. The goal is to take a tiny neuron-level circuit (like the ones in OpenAI's "Sparse Circuits" work) and automatically recover a concise Python program that implements the same algorithm, along with a bounded formal proof that the two are equivalent on a finite token domain. Roughly, the pipeline is: 1. Start from a pruned circuit graph for a specific…
Jan 2026 · github.com · its alternatives →
21
LLMs can be susceptible to a new kind of malware▲17
New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
22
LLM Explained▲6
Simplifies artificial intelligence and LLM for everyone.
2025 · llmexplained.netlify.app · its alternatives →
23
LLM Thought Visualization▲24
To know what models don't say out loud. Contribute to ninjahawk/Subtext development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
24AS
A surprisingly effective way to predict token importance in LLM prompts▲14
We explored a novel method to gauge the significance of tokens in prompts given to large language models, without needing direct model access. Essentially, we just did an ablation study on the prompt using cosine similarity of the embeddings as the measure. We got surprisingly promising results when comparing this really simple approach to integrated gradients. Curious to hear thoughts from the community!
2023 · heatmap.demos.watchful.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 →