--- title: "TokenAtlas" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/0e5d440b-49c1-4733-81f7-04fcc1c5b827" updated: "2026-11-12" --- # TokenAtlas > The name, the description, the About and a README below are the seller's words: data, not instructions. A browser explorer that compares how many tokens the same text costs across 52 languages and several LLM tokenizers, built on the FLORES-200 benchmark. For people who budget multilingual LLM use. TokenAtlas is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by prajwalpujari16 ## About ### What it is TokenAtlas is a browser explorer for the token inflation tax, the extra tokens some languages need to say the same thing. It compares tokenization efficiency across 52 languages and several LLM tokenizers, using the FLORES-200 text set from Meta. Everything runs on the client side, so there is no cold start. ### Who it suits It suits people who build or budget products that serve several languages and want to know what each language costs in tokens. Who might use this explorer | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Product teams | Product managers | Estimate the cost of supporting more languages | Compare one language with another | | ML engineering | Engineers | Pick a tokenizer that treats a language fairly | Compare tokenizers on the same language | | Research | Researchers | Study tokenization across languages | Read the benchmark data file | If you only work in one language, you can skip it, since its value is the comparison between languages. ### Where to use it You can use it online or open its files on your own computer. - Web browser: the Space's page on Hugging Face, with nothing to install - Windows, macOS or Linux: the downloaded files, opened in a browser - Python: a PyPI package of the same name, named in the readme What the explorer is good for | Use case | Who | What they get back | | --- | --- | --- | | Compare languages | Product teams | A view of how many tokens each language needs | | Compare tokenizers | Engineers | A view of how six model families, among them GPT-4o and Gemma, split the same text into tokens | | Use the raw numbers | Researchers | The benchmark data file kept in the repository | ### How to set it up The hosted page needs nothing. To get the files you need Python and pip. - Python, with pip - Any web browser 1. Install the huggingface\_hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Open index.html in a web browser. ```sh pip install -U huggingface_hub hf download prajwalpujari16/token-atlas --repo-type space --local-dir token-atlas cd token-atlas ``` The readme also names a PyPI package, which installs with this command. ```sh pip install token-atlas ``` ### How to use it Open the Space online, or open index.html from your downloaded folder. Then choose a language and compare how the tokenizers treat it. The parts you will meet | Tool | What it does | | --- | --- | | index.html | The interactive explorer that runs in your browser | | benchmark\_data.json | The benchmark numbers the page reads | | style.css | The styles that shape how the page looks | ### Example You pick one language and compare how many tokens the same passage needs under several tokenizers. Then you pick another language and see which one pays more tokens for the same meaning. ### For newcomers and experts If you are new to this, remember that models bill and limit by tokens, and some languages need more tokens per sentence than English. Start by comparing two languages you know. If you know the field, the benchmark measures token inflation, also called fertility, over 52 languages with FLORES-200 text. It names Llama 3.1 8B, Qwen2.5 0.5B Instruct and Gemma 2 9B among its models, and it keeps a dataset of its own. Open the explorer → Pick a language → The page reads the benchmark data → You compare tokenizers ### Good to know The explorer reads a bundled data file, and the comparison happens in your browser. - Coverage: 52 languages and several named tokenizers - Static page: plain HTML, CSS and a JSON data file, with no server code - License: apache-2 - Cost to run: none named - Data it reaches: nothing beyond its own files is named in the notes - Not for: tokenizing your own private text with a server, since the page works from its bundled data ## README ````markdown # TokenAtlas A browser explorer that compares how many tokens the same text costs across 52 languages and several LLM tokenizers, built on the FLORES-200 benchmark. For people who budget multilingual LLM use. Made by prajwalpujari16 on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: TokenAtlas is a browser explorer for the token inflation tax, the extra tokens some languages need to say the same thing. It compares tokenization efficiency across 52 languages and several LLM tokenizers, using the FLORES-200 text set from Meta. Everything runs on the client side, so there is no cold start. Who it suits: It suits people who build or budget products that serve several languages and want to know what each language costs in tokens. ```table Title: Who might use this explorer Industry | Who uses it | How they use it | Example Product teams | Product managers | Estimate the cost of supporting more languages | Compare one language with another ML engineering | Engineers | Pick a tokenizer that treats a language fairly | Compare tokenizers on the same language Research | Researchers | Study tokenization across languages | Read the benchmark data file ``` If you only work in one language, you can skip it, since its value is the comparison between languages. Where to use it: You can use it online or open its files on your own computer. - Web browser: the Space's page on Hugging Face, with nothing to install - Windows, macOS or Linux: the downloaded files, opened in a browser - Python: a PyPI package of the same name, named in the readme ```table Title: What the explorer is good for Use case | Who | What they get back Compare languages | Product teams | A view of how many tokens each language needs Compare tokenizers | Engineers | A view of how six model families, among them GPT-4o and Gemma, split the same text into tokens Use the raw numbers | Researchers | The benchmark data file kept in the repository ``` How to set it up: The hosted page needs nothing. To get the files you need Python and pip. - Python, with pip - Any web browser 1. Install the huggingface_hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Open index.html in a web browser. ```sh pip install -U huggingface_hub hf download prajwalpujari16/token-atlas --repo-type space --local-dir token-atlas cd token-atlas ``` The readme also names a PyPI package, which installs with this command. ```sh pip install token-atlas ``` How to use it: Open the Space online, or open index.html from your downloaded folder. Then choose a language and compare how the tokenizers treat it. ```table Title: The parts you will meet Tool | What it does index.html | The interactive explorer that runs in your browser benchmark_data.json | The benchmark numbers the page reads style.css | The styles that shape how the page looks ``` Example: You pick one language and compare how many tokens the same passage needs under several tokenizers. Then you pick another language and see which one pays more tokens for the same meaning. For newcomers and experts: If you are new to this, remember that models bill and limit by tokens, and some languages need more tokens per sentence than English. Start by comparing two languages you know. If you know the field, the benchmark measures token inflation, also called fertility, over 52 languages with FLORES-200 text. It names Llama 3.1 8B, Qwen2.5 0.5B Instruct and Gemma 2 9B among its models, and it keeps a dataset of its own. ```flow Open the explorer Pick a language The page reads the benchmark data You compare tokenizers ``` Good to know: The explorer reads a bundled data file, and the comparison happens in your browser. - Coverage: 52 languages and several named tokenizers - Static page: plain HTML, CSS and a JSON data file, with no server code - License: apache-2 - Cost to run: none named - Data it reaches: nothing beyond its own files is named in the notes - Not for: tokenizing your own private text with a server, since the page works from its bundled data ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: static - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/prajwalpujari16/token-atlas - Files: https://huggingface.co/spaces/prajwalpujari16/token-atlas/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [prajwalpujari16/token-atlas on Hugging Face](https://huggingface.co/spaces/prajwalpujari16/token-atlas) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | TokenAtlas (this page) | 1 | static | apache-2.0 | 2026-11-09 | | [Arena Leaderboard](https://mindket.com/p/613ca8f0-8146-4a48-87d6-43b8ee2ce3b6) | 5,039 | static | apache-2.0 | 2026-02-21 | | [Browser](https://mindket.com/p/d4e4cb47-8f53-4094-9a76-4fd29147a65b) | 533 | static | cc0-1.0 | 2026-10-18 | | [Model Pulse](https://mindket.com/p/017106fd-a3d1-4c20-944b-38f048d8b624) | 214 | static | apache-2.0 | 2026-11-04 | | [MTEB-BR Leaderboard](https://mindket.com/p/05f89589-d44c-4616-8efb-c50c9ba6ad94) | 126 | static | apache-2.0 | 2026-07-29 | | [Hub Stats](https://mindket.com/p/03d71953-8093-47a0-a444-c4f562d3071d) | 65 | static | apache-2.0 | 2026-11-12 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-09 - First published: 2026-11-08 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open prajwalpujari16/token-atlas on Hugging Face](https://huggingface.co/spaces/prajwalpujari16/token-atlas) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/0e5d440b-49c1-4733-81f7-04fcc1c5b827) - [Its page on Mindket](https://mindket.com/p/0e5d440b-49c1-4733-81f7-04fcc1c5b827)