Skip to main content

TokenAtlas 🌐

Universal Multilingual Tokenizer Benchmark & Global Inflation Atlas

PyPI License Python 3.12+ CI

TokenAtlas is an open-source benchmarking engine and diagnostic suite that measures the token inflation tax across global languages and frontier LLM tokenizers using Meta's FLORES-200 parallel evaluation corpus.


⚡ The Problem: The Hidden Token Tax

Large Language Model tokenizers (like BPE, Tiktoken, and WordPiece) are trained predominantly on English datasets. Expressing the exact same thought in other languages requires significantly more tokens.

This creates 4 compounding penalties for international users:

  1. Financial Tax: APIs bill strictly per token. Multilingual conversations cost up to $4\times$ more per 1k words.
  2. Context Shrinkage: A 128k context window is effectively cut to ~30k words for high-inflation languages.
  3. TTFT Latency Penalty: Attention prefill latency scales with sequence token length.
  4. VRAM Footprint: Paged KV-cache memory allocators must reserve more physical blocks per user session.

🚀 Quickstart

Installation

pip install token-atlas-engine

1. Compare Tokenizers on Single String

token-atlas compare --text "ここでテキストを分かち書きします" --tokenizers gpt-4o,gpt-4 --language ja

2. Run Multilingual Parallel Benchmark

# Benchmark all 28 languages across models
token-atlas bench --tokenizers gpt-4o,gpt-4 --languages all --samples 5

# Benchmark with custom parallel corpus JSON
token-atlas bench --tokenizers deepseek-v3,mistral-tekken --custom-corpus my_corpus.json

3. Compare Text from File or String

token-atlas compare --file document.txt --tokenizers gpt-4o,mistral-tekken --language kn

4. Tokenizer-Aware Model Routing (Cut Effective Costs)

# Analyze prompt script and recommend the most token-efficient model
token-atlas route --text "ದಯವಿಟ್ಟು ಈ ದಾಖಲೆಯನ್ನು ವಿಶ್ಲೇಷಿಸಿ ಮತ್ತು ಕನ್ನಡದಲ್ಲಿ ವರದಿ ನೀಡಿ"

5. Lossless Prompt Token Minification (Save 15-35% on Bills)

# Minify prompt whitespace and embedded JSON schemas before model dispatch
token-atlas minify --file agent_prompt.txt --out minified_prompt.txt

6. Benchmark Multi-Domain Inflation (Code, Indentation, Tools, Math)

# Benchmark tool-calling schema tax (verbose vs compact JSON)
token-atlas bench-domain --domain tools --tokenizers gpt-4o,gpt-4

# Benchmark indentation tax (4-space vs 2-space vs tabs vs minified)
token-atlas bench-domain --domain indentation --tokenizers gpt-4o,gpt-4

# Benchmark cross-language code syntax
token-atlas bench-domain --domain code --tokenizers gpt-4o,gpt-4

7. Diagnose UTF-8 Byte Fragmentation

token-atlas explain-bytes --text "ಕನ್ನಡ"

8. Python Production API

from token_atlas import recommend_model, minify_prompt

# 1. Route to the most cost-effective model for the detected script
decision = recommend_model(
    prompt="ದಯವಿಟ್ಟು ಈ ದಾಖಲೆಯನ್ನು ವಿಶ್ಲೇಷಿಸಿ...",
    budget_tier="frugal"
)
print(f"Recommended: {decision.recommended_model} ({decision.savings_vs_worst} cheaper)")

# 2. Minify prompt whitespace and embedded JSON losslessly
minified = minify_prompt(raw_prompt)
print(f"Saved {minified.tokens_saved} tokens ({minified.token_reduction_pct}% reduction)")

9. Export Standalone Interactive Web Atlas

token-atlas export-web --out-dir docs/

10. List Supported Tokenizers & Language Families

token-atlas list-tokenizers
token-atlas list-tokenizers --category code
token-atlas list-languages

🌐 Interactive Web Atlas & Live Demo

TokenAtlas exports a zero-dependency, self-contained interactive web application with:

  • Real-time sorting and filtering by language family and token inflation index.
  • Cross-model head-to-head comparison table.
  • Live Token Tax & Context Shrinkage Calculator with interactive preset prompts.

Live GitHub Pages Deployment: prajwal7-2002.github.io/token-atlas


📚 Educational Guide: How Tokenizers Work

For a first-principles breakdown of Byte-Pair Encoding (BPE), UTF-8 byte fallback mechanics, and the vocabulary VRAM scaling equation ($V \times d_{\text{model}}$), see: 👉 docs/learn-tokenizers.md


📊 Core Metrics

TokenAtlas rigorously evaluates 4 dimensions on identical parallel sentences:

  • Token Inflation Index ($\tau$):
    $$\tau(L, M) = \frac{\text{Tokens in Language } L}{\text{Tokens in English}}$$
  • Bytes Per Token (BPT): Compression density of information per token ($BPT = \text{Bytes} / \text{Tokens}$).
  • Effective Context Window ($W_{\text{eff}}$): Real usable context in equivalent English tokens ($W_{\text{eff}} = \text{ContextLimit} / \tau$).
  • Cost Multiplier ($\kappa$): Financial invoice scaling factor per 1k semantic words.

🔬 Evaluated Frontier Tokenizers

Tokenizer Vocab Size Context Limit Category Target Architecture & Focus
OpenAI GPT-4o (o200k_base) 200,000 128,000 Multilingual Frontier Multilingual Tiktoken
Mistral Tekken 131,072 128,000 Multilingual Balanced Multilingual BPE (Mistral-Nemo-Instruct-2407)
Cohere Aya Expanse 256,000 128,000 Multilingual 101-Language Global Tokenizer with massive Dravidian/African merges
DeepSeek-R1 & V3 128,815 128,000 Reasoning Sinitic-first Byte BPE ($\tau = 0.98\times$ on Chinese) & Reasoning
Qwen 2.5 152,064 131,072 Multilingual High-capacity Asian & Multilingual Byte BPE
Qwen 2.5 Coder 152,064 131,072 Code Specialized syntax, indentation, and repo path compression
Google Gemma 2 256,000 8,192 General Ultra-large Vocab SentencePiece
Meta Llama 3.1 128,256 128,000 General Latin-first Tiktoken BPE
Meta Llama 3.2 128,256 128,000 SLM Edge-optimized Latin-first BPE
HuggingFace SmolLM2 49,152 8,192 SLM Ultra-compact 49k vocabulary minimizing embedding memory
OpenAI GPT-4 (cl100k_base) 100,277 128,000 General English-biased Baseline Tiktoken

🌍 Supported Language Coverage (52 Languages)

TokenAtlas evaluates 52 global languages across 12 linguistic families aligned to FLORES-200:

  • Germanic & Romance: English (en), German (de), Dutch (nl), Swedish (sv), Danish (da), Norwegian (no), French (fr), Spanish (es), Italian (it), Portuguese (pt), Romanian (ro)
  • Slavic: Russian (ru), Ukrainian (uk), Polish (pl), Czech (cs), Bulgarian (bg), Serbian (sr), Croatian (hr)
  • Hellenic & Finno-Ugric: Greek (el), Finnish (fi), Hungarian (hu)
  • Semitic & Middle Eastern: Arabic (ar), Hebrew (he), Amharic (am), Persian (fa)
  • Turkic: Turkish (tr), Azerbaijani (az), Uzbek (uz), Kazakh (kk)
  • Indic (Indo-Aryan): Hindi (hi), Bengali (bn), Marathi (mr), Urdu (ur), Gujarati (gu), Punjabi (pa), Nepali (ne), Sinhala (si)
  • Indic (Dravidian): Kannada (kn), Tamil (ta), Telugu (te), Malayalam (ml)
  • CJK: Simplified Chinese (zh), Traditional Chinese (zh-tw), Japanese (ja), Korean (ko)
  • Southeast Asian & Austronesian: Vietnamese (vi), Thai (th), Indonesian (id), Malay (ms), Filipino (tl)
  • African: Swahili (sw), Yoruba (yo)

🛠️ Developer Setup & Testing

# Clone repository
git clone https://github.com/Prajwal7-2002/token-atlas.git
cd token-atlas

# Run test suite
uv run pytest

📜 Citation

If you use TokenAtlas in your research or benchmarks, please cite:

@software{Pujari_TokenAtlas_2026,
  author = {Pujari, Prajwal},
  title = {{TokenAtlas: Universal Multilingual Tokenizer Benchmark & Global Inflation Atlas}},
  year = {2026},
  url = {https://github.com/Prajwal7-2002/token-atlas},
  license = {Apache-2.0}
}

License

Apache 2.0 © 2026 Prajwal Pujari. See LICENSE for details.

Metadata

Release files for token-atlas-engine 0.3.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for token-atlas-engine 0.3.0
File Size Uploaded Provenance Actions
token_atlas_engine-0.3.0.tar.gz 62.8 kB With provenance Details for token_atlas_engine-0.3.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for token-atlas-engine 0.3.0
File Interpreter ABI Platform Actions
token_atlas_engine-0.3.0-py3-none-any.whl Python 3 none any Details for token_atlas_engine-0.3.0-py3-none-any.whl

Total release size: 129.7 kB

Release files / token_atlas_engine-0.3.0.tar.gz

Download URL token_atlas_engine-0.3.0.tar.gz
Size 62.8 kB
Tags Source
SHA-256 checksum
How to use checksums
6e1c56757a9be08040c11cd772ef01cb3ccdbad667c097e8c9fa6d3c4ea3d66e
BLAKE2b-256 checksum
How to use checksums
bfca6775f47481a372c98a1d6784947429089a9f255ef9e40dd22296e8f7be94
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 12, 2026.

Transparency log

Release files / token_atlas_engine-0.3.0-py3-none-any.whl

Download URL token_atlas_engine-0.3.0-py3-none-any.whl
Size 66.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
7361060cdf8302abb94d14db8d4540f233cc96a69d3ec4ab7367eb2a85556a7a
BLAKE2b-256 checksum
How to use checksums
358f345d3fe58740a5903f550cc72b4ce7e326c3df1a24ba890a5135db0cbba4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 12, 2026.

Transparency log

Security for token-atlas-engine 0.3.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

Both files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for token_atlas_engine-0.3.0.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 12, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.3.0 This release

2 release files Full provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page