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⇱ AMD Ryzen 7 8700G Linux Performance Review - Phoronix

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AMD Ryzen 7 8700G Linux Performance

Written by Michael Larabel in Processors on 29 January 2024 at 09:00 AM EST. Page 7 of 11. 97 Comments.

👁 Llamafile benchmark with settings of Test: mistral-7b-instruct-v0.2.Q8_0, Acceleration: CPU. Ryzen 7 8700G - 2400MHz FCLK was the fastest.

👁 Llamafile benchmark with settings of Test: llava-v1.5-7b-q4, Acceleration: CPU. Ryzen 7 8700G - 2400MHz FCLK was the fastest.

👁 Llama.cpp benchmark with settings of Model: llama-2-7b.Q4_0.gguf. Ryzen 7 8700G - 2400MHz FCLK was the fastest.

👁 Whisper.cpp benchmark with settings of Model: ggml-base.en, Input: 2016 State of the Union. Ryzen 7 7700X was the fastest.

👁 Whisper.cpp benchmark with settings of Model: ggml-base.en, Input: 2016 State of the Union. Ryzen 7 7700X was the fastest.

👁 Whisper.cpp benchmark with settings of Model: ggml-small.en, Input: 2016 State of the Union. Ryzen 7 7700X was the fastest.

👁 PyTorch benchmark with settings of Device: CPU, Batch Size: 1, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 PyTorch benchmark with settings of Device: CPU, Batch Size: 64, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 1, Model: VGG-16. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 1, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 1, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 1, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 64, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 64, Model: ResNet-50. Ryzen 7 7700X was the fastest.

👁 TensorFlow benchmark with settings of Device: CPU, Batch Size: 64, Model: ResNet-50. Ryzen 7 7700X was the fastest.

The Ryzen Zen 4 CPUs were also performing well in other workloads like Llamafile, Whisper.cpp, PyTorch, and TensorFlow.

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