Intel Core Ultra 5 245K Linux Performance

Written by Michael Larabel in Processors on 25 October 2024 at 11:16 AM EDT. Page 7 of 11. 42 Comments.
PyBench benchmark with settings of Total For Average Test Times. Core Ultra 9 285K @ DDR5-8000 was the fastest.
PyBench benchmark with settings of Total For Average Test Times. Core Ultra 9 285K @ DDR5-8000 was the fastest.
PyPerformance benchmark with settings of Benchmark: async_tree_io. Core Ultra 9 285K @ DDR5-8000 was the fastest.
PyPerformance benchmark with settings of Benchmark: asyncio_websockets. Core Ultra 9 285K was the fastest.
PyPerformance benchmark with settings of Benchmark: crypto_pyaes. Core Ultra 9 285K @ DDR5-8000 was the fastest.
PyPerformance benchmark with settings of Benchmark: django_template. Core Ultra 9 285K @ DDR5-8000 was the fastest.
PyPerformance benchmark with settings of Benchmark: json_loads. Core Ultra 9 285K was the fastest.
PyPerformance benchmark with settings of Benchmark: regex_compile. Core Ultra 9 285K was the fastest.

For those running a lot of single-threaded Python scripts, the Arrow Lake processors were delivering leading performance at low power.

simdjson benchmark with settings of Throughput Test: PartialTweets. Ryzen 9 9900X was the fastest.
simdjson benchmark with settings of Throughput Test: Kostya. Ryzen 7 9700X @ 105W cTDP was the fastest.

But with software like simdjson that employs AVX-512 for faster JSON parsing, the AMD Ryzen processors returned to leading the race.

Numpy Benchmark benchmark with settings of . Ryzen 7 9700X was the fastest.
Numpy Benchmark benchmark with settings of . Ryzen 7 9700X was the fastest.
Numpy Benchmark benchmark with settings of . Ryzen 7 9700X was the fastest.

The Ryzen 9000 series are much better for those doing a lot of work with Numpy.

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