{"library":"simsimd","type":"library","category":null,"description":"SimSIMD is a highly optimized, mixed-precision math library providing over 350 SIMD-accelerated kernels for common vector similarity functions and dot-products. It is extensively used in AI, Search, and Database Management Systems workloads to achieve significant performance and accuracy improvements over standard NumPy and SciPy operations. The library is actively developed with frequent releases, though its main development has transitioned to a new project name, NumKong, starting with version 7.x.x.","language":"python","status":"active","version":"6.5.16","tags":["vector math","SIMD","performance","BLAS-like","AI","machine learning","vector database","distance metrics","similarity functions"],"install":[{"cmd":"pip install simsimd","imports":["import simsimd"]}],"homepage":"https://simsimid.com","github":"https://github.com/ashvardanian/simsimd","docs":null,"changelog":null,"pypi":"https://pypi.org/project/simsimd/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":2.1,"avg_import_s":0,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/simsimd/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}