--- license: cc-by-4.0 language: - en pretty_name: Token cost by programming language (Claude, Gemini, GPT) size_categories: - n<1K tags: - code - programming-languages - tokenizer - llm-cost - claude - gemini - gpt configs: - config_name: default data_files: - split: train path: token-cost-by-programming-language.csv --- # Token cost by programming language: the same programs in 10 languages on Claude, Gemini and GPT Two small programs (an inventory class and Dijkstra's shortest path) written in Python, Ruby, JavaScript, TypeScript, PHP, Rust, Java, C++, Go and C, with input tokens counted on Claude Opus/Sonnet 5.5, Claude Haiku 4.5, Gemini 3.x and GPT (o200k_base). **Headline:** both programs together cost 809 GPT tokens in Python and 1,536 in C (+90%). Python and Ruby were the cheapest on every tokenizer; Go and C the most expensive. Claude 5.5 needed 43% to 59% more tokens than GPT for the same code. - Source page, chart and method: https://tokensave.app/data/token-cost-by-programming-language - Related: token cost by data format (https://tokensave.app/data/token-cost-by-format) - DOI (Zenodo): [10.5281/zenodo.23446563](https://doi.org/10.5281/zenodo.23446563) - Also on: [Hugging Face](https://huggingface.co/datasets/JOHNISKING/token-cost-by-programming-language) · [Kaggle](https://www.kaggle.com/datasets/johnisking/token-cost-by-programming-language) - Measured: 2026-10-18 - License: CC BY 4.0 ## Key findings - Python and Ruby are the cheapest: 809 and 819 GPT tokens. JavaScript needs +20%, Java +50%, Go +68% and C +90%. - The ranking holds on every tokenizer tested. - Claude 5.5 costs 43% to 59% more than GPT for the same code (largest gap: Java). Gemini needs 12% to 25% more than GPT. - Types add tokens: TypeScript needs 11% more GPT tokens than the same JavaScript. - File size is a rough guide only: Java has the most characters, but Go and C need more tokens. ## Files - `token-cost-by-programming-language.csv`: one row per language and program (`inventory`, `dijkstra` and `total`) with `language, program, characters, lines, claude55_tokens, claude45_tokens, gemini_tokens, gpt_tokens` - `token-cost-by-programming-language.json`: the same data plus all 20 source files, so every count can be reproduced ## Data (both programs together) | Language | Characters | Claude Opus/Sonnet 5.5 | Claude Haiku 4.5 | Gemini 3.x | GPT (o200k) | GPT vs Python | |---|---:|---:|---:|---:|---:|---:| | Python | 2,887 | 1,176 | 970 | 963 | 809 | ±0% | | Ruby | 2,478 | 1,181 | 961 | 944 | 819 | +1% | | JavaScript | 3,195 | 1,442 | 1,199 | 1,184 | 967 | +20% | | TypeScript | 3,610 | 1,590 | 1,311 | 1,288 | 1,070 | +32% | | PHP | 3,697 | 1,609 | 1,311 | 1,262 | 1,128 | +39% | | Rust | 4,081 | 1,815 | 1,452 | 1,411 | 1,189 | +47% | | Java | 5,101 | 1,934 | 1,551 | 1,511 | 1,217 | +50% | | C++ | 4,793 | 1,933 | 1,626 | 1,617 | 1,343 | +66% | | Go | 4,292 | 2,143 | 1,749 | 1,701 | 1,359 | +68% | | C | 4,843 | 2,219 | 1,859 | 1,820 | 1,536 | +90% | ## Method 1. Each program written idiomatically in each language with no comments. Every version was compiled or run and printed exactly the same output as the Python version. 2. Claude: each file sent through Claude Code (`claude -p`) with a fixed one-line system prompt; input tokens minus the same run with a one-character message. Opus 5.5 and Sonnet 5.5 gave identical counts; a re-run gave identical counts. 3. Gemini: Google AI Studio prompt token counter on Gemini 3.8 Flash, minus its one start token. 4. GPT: tiktoken with `o200k_base`. ## Limitations - Two small programs. Comments, long names or boilerplate in real projects can shift the numbers; the ranking is more stable than the exact percentages. - Coding style changes the count within a language. - Input tokens only; not a measure of how well each model writes each language. ## Citation TokenSave (2026). Token cost by programming language: the same programs in 10 languages on Claude, Gemini and GPT [Data set]. Zenodo. https://doi.org/10.5281/zenodo.23446563 Count tokens for your own code at [tokensave.app](https://tokensave.app/).