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AI · alternatives · 2026

24 alternatives to TokScope

Interactive Token Embedding Visualization Tool of LLMs

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1WT

    After working with LLMs for long enough, I found myself wanting a lightweight utility for doing various small tasks to prepare inputs, locate information and create evaluators. This library is two things: a very simple model and utilities that inference it (eg. fuzzy deduplication). The target platform is CPU, and it’s intended to be light, fast and pip installable — a library that lowers the barrier to working with strings semantically. You don’t need to install pytorch to use it, or any deep learning runtimes. How can this be accomplished? The model is simply token embeddings that are…

    2024 · github.com · its alternatives →

  2. 2FC

    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 →

  3. 3
    LangWatch▲669

    Understand, measure and improve your LLMs

    2024 · langwatch.ai · its alternatives →

  4. 4LC

    Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…

    2023 · github.com · its alternatives →

  5. 5

    Compute & interactively visualize large embeddings

    2025 · apple.github.io · its alternatives →

  6. 6KG

    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 →

  7. 7CA

    Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)

    2023 · chainforge.ai · its alternatives →

  8. 8VI

    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 →

  9. 9UL

    Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…

    2023 · github.com · its alternatives →

  10. 10SW

    Hey - I've been playing with LLMs since GPT-2 and recently experimented with fully generative UIs where the HTML/Canvas are generated just-in-time. Every post on the feed( on slop/duck/storytime) you see is streamed and generated just-in-time with HTML and into a Canvas with Gemini 3 Flash. Comments and DMs are bidirectionally linked with a Cloudflare Workers Durable Object which is why they feel so fast. Every generated post is saved into a DO SQLite which is then served into the "Following" feed so it can be served quicker. This was inspired by Wikitok, a VSCode Extension I…

    Jan 2026 · quack.sdan.io · its alternatives →

  11. 11TA

    TokenDagger is a drop-in replacement for OpenAI’s Tiktoken (the tokenizer behind Llama 3, Mistral, GPT-3.*, etc.). It’s written in C++ 17 with thin Python bindings, keeps the exact same BPE vocab/special-token rules, and focuses on raw speed. I’m teaching myself LLM internals by re-implementing the stack from first principles. Profiling TikToken’s Python/Rust implementation showed a lot of time was spent doing regex matching. Most of my perf gains come from a) using a faster jit-compiled regex engine; and b) simplifying the algorithm to forego regex matching special tokens at all.…

    2025 · github.com · its alternatives →

  12. 12

    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 →

  13. 13

    Google's first natively multimodal embedding model

    Mar 2026 · blog.google · its alternatives →

  14. 14HL

    All content is based on Andrej Karpathy's "Intro to Large Language Models" lecture (youtube.com/watch?v=7xTGNNLPyMI). I downloaded the transcript and used Claude Code to generate the entire interactive site from it — single HTML file. I find it useful to revisit this content time to time.

    Apr 2026 · ynarwal.github.io · its alternatives →

  15. 15WV

    Inspectus allows you to create interactive visualizations of attention matrices with just a few lines of Python code. It’s designed to run smoothly in Jupyter notebooks through an easy-to-use Python API. Inspectus provides multiple views to help you understand language model behaviors. If you have any questions, feel free to ask!

    2024 · github.com · its alternatives →

  16. 16

    Tokenization visualization tool for llms

    2025 · its alternatives →

  17. 17FG

    We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.

    2023 · github.com · its alternatives →

  18. 18

    Find your best LLM for a local inference

    2023 · its alternatives →

  19. 19KO

    We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…

    2025 · github.com · its alternatives →

  20. 20IG
  21. 21LT
  22. 22YD

    If you've built any web-based app in the last 15 years, you probably used something like Datadog, New Relic, Sentry, etc. to monitor and trace your app, right? Why should it be different when the app you're building happens to be using LLMs? So today we're open-sourcing OpenLLMetry-JS. It's an open protocol and SDK, based on OpenTelemetry, that provides traces and metrics for LLM JS/TS applications and can be connected to any of the 15+ tools that already support OpenTelemetry. Here's the repo: https://github.com/traceloop/openllmetry-js A few months ago we launched…

    2024 · github.com · its alternatives →

  23. 23LS

    I built this library because langchain was too bloated and I needed a simple abstraction to call multiple LLM APIs. litellm has two functions - completion(), embedding()

    2023 · github.com · its alternatives →

  24. 24AS

    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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