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Low Latency CPU Inference on AMD EPYC Processors

Source: AMD•November 6, 2026 at 03:52 PM

Low Latency CPU Inference on AMD EPYC Processors

Optimize BERT-Base CPU inference on AMD EPYC™ processors with ZenDNN and zentorch, delivering up to 47.3% average gains over ONNX Runtime.

Footnotes and Disclaimers

Testing by AMD as of September 2026

ZD-070: BERT-Base Uncased inference, zentorch FP32 versus ONNX Runtime FP32, on AMD EPYC™ 9654 (96 cores, 1 socket, SMT on, NPS4); ZenDNN 6.0, zentorch 2.13.0.0, ONNX Runtime 1.17.0; Hugging Face BERT-Base Uncased; sequence lengths 32/64/128; 1, 2, 4, 6 instances at 8 and 16 cores; physical cores; median of 10 runs. Single-instance average 11.4%; multi-instance average 9.0%; all-configuration average 9.7%; peak 29.5% at 1 instance(s), sequence length 64, 16 cores. zentorch leads on 14, on par on 4, trails on 3 of 21. Per-workload latency gain versus ONNX Runtime (higher is better; instances=1 is single-instance, 2/4/6 are multi-instance): instances seqlen cores latency_gain% 1 32 8 -1.9% 1 32 16 -1.1% 1 64 8 +8.6% 1 64 16 +29.5% 1 128 8 +7.0% 1 128 16 +26.1% 2 32 8 -3.0% 2 32 16 +1.6% 2 64 8 +7.9% 2 64 16 +28.9% 2 128 8 +6.5% 2 128 16 +26.4% 4 32 8 -6.6% 4 32 16 +1.7% 4 64 8 +6.0% 4 64 16 +27.6% 4 128 8 +6.0% 4 128 16 +25.2% 6 32 8 -5.9% 6 64 8 +6.3% 6 128 8 +6.6% Results may vary due to factors including system configurations, software versions and BIOS settings.

ZD-071: BERT-Base Uncased inference, zentorch BF16 versus ONNX Runtime FP32, on AMD EPYC™ 9654 (96 cores, 1 socket, SMT on, NPS4); ZenDNN 6.0, zentorch 2.13.0.0, ONNX Runtime 1.17.0; Hugging Face BERT-Base Uncased; sequence lengths 32/64/128; 1, 2, 4, 6 instances at 8 and 16 cores; physical cores; median of 10 runs. Single-instance average 47.5%; multi-instance average 47.2%; all-configuration average 47.3%; peak 58.1% at 4 instance(s), sequence length 128, 16 cores. zentorch leads on 21, on par on 0, trails on 0 of 21. Per-workload latency gain versus ONNX Runtime (higher is better; instances=1 is single-instance, 2/4/6 are multi-instance): instances seqlen cores latency_gain% 1 32 8 +35.9% 1 32 16 +41.1% 1 64 8 +46.0% 1 64 16 +57.2% 1 128 8 +47.7% 1 128 16 +57.3% 2 32 8 +35.9% 2 32 16 +43.3% 2 64 8 +46.1% 2 64 16 +57.1% 2 128 8 +47.8% 2 128 16 +57.7% 4 32 8 +36.7% 4 32 16 +44.7% 4 64 8 +45.4% 4 64 16 +57.2% 4 128 8 +47.7% 4 128 16 +58.1% 6 32 8 +37.0% 6 64 8 +45.6% 6 128 8 +47.8% Results may vary due to factors including system configurations, software versions and BIOS settings.

ZD-072: BERT-Base Uncased inference, zentorch FP32 versus ONNX Runtime FP32, on AMD EPYC™ 9V74 (80 cores, 1 socket, SMT on, NPS5, Hyper-V VM); ZenDNN 6.0, zentorch 2.13.0.0, ONNX Runtime 1.17.0; Hugging Face BERT-Base Uncased; sequence lengths 32/64/128; 1, 2, 4, 6 instances at 8 and 16 cores; physical cores; median of 10 runs. Single-instance average 11.1%; multi-instance average 8.3%; all-configuration average 9.1%; peak 31.2% at 1 instance(s), sequence length 64, 16 cores. zentorch leads on 14, on par on 3, trails on 4 of 21. Per-workload latency gain versus ONNX Runtime (higher is better; instances=1 is single-instance, 2/4/6 are multi-instance): instances seqlen cores latency_gain% 1 32 8 -4.2% 1 32 16 +1.3% 1 64 8 +7.2% 1 64 16 +31.2% 1 128 8 +5.8% 1 128 16 +25.1% 2 32 8 -4.6% 2 32 16 +1.0% 2 64 8 +6.8% 2 64 16 +30.7% 2 128 8 +5.7% 2 128 16 +25.0% 4 32 8 -4.6% 4 32 16 -0.6% 4 64 8 +6.7% 4 64 16 +25.4% 4 128 8 +5.5% 4 128 16 +20.4% 6 32 8 -4.8% 6 64 8 +5.4% 6 128 8 +5.8% Results may vary due to factors including system configurations, software versions and BIOS settings.

ZD-073: BERT-Base Uncased inference, zentorch BF16 versus ONNX Runtime FP32, on AMD EPYC™ 9V74 (80 cores, 1 socket, SMT on, NPS5, Hyper-V VM); ZenDNN 6.0, zentorch 2.13.0.0, ONNX Runtime 1.17.0; Hugging Face BERT-Base Uncased; sequence lengths 32/64/128; 1, 2, 4, 6 instances at 8 and 16 cores; physical cores; median of 10 runs. Single-instance average 47.0%; multi-instance average 45.7%; all-configuration average 46.1%; peak 58.1% at 1 instance(s), sequence length 64, 16 cores. zentorch leads on 21, on par on 0, trails on 0 of 21. Per-workload latency gain versus ONNX Runtime (higher is better; instances=1 is single-instance, 2/4/6 are multi-instance): instances seqlen cores latency_gain% 1 32 8 +34.2% 1 32 16 +40.3% 1 64 8 +45.1% 1 64 16 +58.1% 1 128 8 +47.3% 1 128 16 +57.1% 2 32 8 +33.8% 2 32 16 +39.5% 2 64 8 +44.9% 2 64 16 +57.5% 2 128 8 +47.2% 2 128 16 +57.0% 4 32 8 +34.0% 4 32 16 +39.8% 4 64 8 +44.7% 4 64 16 +56.1% 4 128 8 +47.1% 4 128 16 +56.1% 6 32 8 +34.0% 6 64 8 +45.5% 6 128 8 +48.6% Results may vary due to factors including system configurations, software versions and BIOS settings.

ZD-074: BERT-Base Uncased inference on AMD EPYC™ 9654 (96 cores, 1 socket, SMT on, NPS4); ZenDNN 6.0, zentorch 2.13.0.0, ONNX Runtime 1.17.0; Hugging Face BERT-Base Uncased; sequence lengths 32/64/128; 1, 2, 4, 6 instances at 8 and 16 cores; physical cores; median of 10 runs. Across 42 configurations (FP32 21 + BF16 vs ONNX FP32 21), zentorch wins 35 (83%), on par 4 (10%), loses 3 (7%). Per-workload latency gain versus ONNX Runtime (higher is better): instances seqlen cores FP32_gain% BF16_gain% 1 32 8 -1.9% +35.9% 1 32 16 -1.1% +41.1% 1 64 8 +8.6% +46.0% 1 64 16 +29.5% +57.2% 1 128 8 +7.0% +47.7% 1 128 16 +26.1% +57.3% 2 32 8 -3.0% +35.9% 2 32 16 +1.6% +43.3% 2 64 8 +7.9% +46.1% 2 64 16 +28.9% +57.1% 2 128 8 +6.5% +47.8% 2 128 16 +26.4% +57.7% 4 32 8 -6.6% +36.7% 4 32 16 +1.7% +44.7% 4 64 8 +6.0% +45.4% 4 64 16 +27.6% +57.2% 4 128 8 +6.0% +47.7% 4 128 16 +25.2% +58.1% 6 32 8 -5.9% +37.0% 6 64 8 +6.3% +45.6% 6 128 8 +6.6% +47.8% Results may vary due to factors including system configurations, software versions and BIOS settings.

ZD-075: BERT-Base Uncased inference on AMD EPYC™ 9V74 (80 cores, 1 socket, SMT on, NPS5, Hyper-V VM); ZenDNN 6.0, zentorch 2.13.0.0, ONNX Runtime 1.17.0; Hugging Face BERT-Base Uncased; sequence lengths 32/64/128; 1, 2, 4, 6 instances at 8 and 16 cores; physical cores; median of 10 runs. Across 42 configurations (FP32 21 + BF16 vs ONNX FP32 21), zentorch wins 35 (83%), on par 3 (7%), loses 4 (10%). Per-workload latency gain versus ONNX Runtime (higher is better): instances seqlen cores FP32_gain% BF16_gain% 1 32 8 -4.2% +34.2% 1 32 16 +1.3% +40.3% 1 64 8 +7.2% +45.1% 1 64 16 +31.2% +58.1% 1 128 8 +5.8% +47.3% 1 128 16 +25.1% +57.1% 2 32 8 -4.6% +33.8% 2 32 16 +1.0% +39.5% 2 64 8 +6.8% +44.9% 2 64 16 +30.7% +57.5% 2 128 8 +5.7% +47.2% 2 128 16 +25.0% +57.0% 4 32 8 -4.6% +34.0% 4 32 16 -0.6% +39.8% 4 64 8 +6.7% +44.7% 4 64 16 +25.4% +56.1% 4 128 8 +5.5% +47.1% 4 128 16 +20.4% +56.1% 6 32 8 -4.8% +34.0% 6 64 8 +5.4% +45.5% 6 128 8 +5.8% +48.6% Results may vary due to factors including system configurations, software versions and BIOS settings.

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