Porting Llama2 to Mojo: Massive Performance Boosts and Insights
Former Meta engineer Aydyn Tairov quickly ported the Python implementation of Llama2 to the newly released Mojo language, demonstrating that Mojo’s SIMD primitives can accelerate Python code by up to 250 times and even make the Python version run 20% faster than the original C implementation.
Aydyn Tairov, an open‑source contributor and former Meta engineer, previously ported the pure C implementation llama2.c of the Llama 2 model to Python, creating llama2.py .
Last week the Mojo programming language was officially released for download, with claims of being up to 68,000 × faster than Python.
Mojo, developed by Modular AI, combines Python’s ease of use with C‑level portability and performance, targeting AI research and production.
Motivated by these claims, Tairov swiftly ported llama2.py to Mojo, producing llama2.mojo , and observed surprising performance gains.
He reported that Mojo’s SIMD primitives boosted the previously poor Python performance by nearly 250 ×, and that, thanks to a vectorized matmul helper, the Python version now runs about 20 % faster than the original C implementation.
For more details, see the GitHub repository https://github.com/tairov/llama2.mojo and the related Twitter post https://twitter.com/tairov/status/1701194900228764023 .
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