AI BriefingGigatoken (GitHub Repository)
Key point
Gigatoken is an open-source tokenizer that delivers speeds up to 1353x faster than the HuggingFace tokenizer.
Details
Gigatoken is an ultra-fast tokenizer specialized for language model training data preprocessing, and it can be installed with pip install gigatoken. It supports compatibility modes with HuggingFace Tokenizers and Tiktoken, allowing it to be applied immediately with minimal changes to existing code.
Benchmark results showed processing speeds of 8,327 MB/s on an Apple M4 Max (16-core) and 24,532 MB/s on an AMD EPYC 9565 (144-core). On the EPYC, this is 989x faster than HuggingFace, and at this speed, the entire Common Crawl (approximately 130 trillion tokens) could be tokenized in 6.5 hours.
There are two key drivers behind this speed improvement:
- Eliminating dependency on regex engines by leveraging SIMD and other techniques during the pretokenization stage
- Pretoken caching optimization that minimizes overhead when repeatedly processing the same words
The Rust-implemented multithreaded backend delivers maximum performance when using the native API (encode_files) that reads files directly, and even in compatibility mode it offers much faster speeds than before. It shows consistent performance across both x86 and ARM-based modern CPUs.
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