Performance Index
Intel® Core™ Processors (Series 3)
| Series | Use Case | Claim | Processor | Systems Measured | Measurement | Measurement Period |
|---|---|---|---|---|---|---|
| 300 | Network Optix: People and vehicle detection throughput (High Accuracy, 640x640 resolution) | With Intel Core Series 3, inference is offloaded to the NPU, allowing GPU and NPU to operate in parallel and keeping the pipeline balanced. This reduces resource contention and delivers more consistent performance under sustained workloads. In our full pipeline testing with Nx AI Manager, this resulted in over 3x higher throughput and more than 3x the number of supported camera streams per system. | Intel® Core™ 5 processor 320 | System 1: Intel® Core™ 5 processor 320 32GB Ubuntu 24.04 LTS System 2: Intel® Core™ 3 100U 64GB Ubuntu 24.04 LTS | System 1: Throughput: 139 FPS System 2: Throughput: 43 FPS | As of Jun 2026 |
| 300 | Network Optix: Number of video streams (High Accuracy, 640x640 resolution) | With Intel Core Series 3, inference is offloaded to the NPU, allowing GPU and NPU to operate in parallel and keeping the pipeline balanced. This reduces resource contention and delivers more consistent performance under sustained workloads. In our full pipeline testing with Nx AI Manager, this resulted in over 3x higher throughput and more than 3x the number of supported camera streams per system. | Intel® Core™ 5 processor 320 | System 1: Intel® Core™ 5 processor 320 32GB Ubuntu 24.04 LTS System 2: Intel® Core™ 3 100U 64GB Ubuntu 24.04 LTS | System 1: 10 streams System 2: 3 streams | As of Jun 2026 |
| 300 | Edge Video Analytics Workload | The Intel® Core™ 7 350 is up to 2.2x faster in end to end video analytics than NVIDIA Jetson Orin™ Nano | Intel® Core™ 7 350 processor | System 1: Intel® Core™ 7 350, Test Date: April 2026, OEM / System: Intel Corporation Wildcat Lake Client Platform, 0.1, Model: Intel Corporation WCL DDR5 Embedded CRB, CPU: Intel(R) Core(TM) 7 350, Cores/Threads: 6, L3 Cache: 6 MB, TDP: 15W, Intel Turbo Boost: Enabled, Base Frequency: 1.5 GHz, Maximum Frequency: 4.8 GHz, Memory: 32GB (1x32GB DDR5 6400MT/s [6400MT/s]), Storage: 1x 465.8G Sabrent SB-RKT4P-500, OS : WCLPFWI1.R00.3515.D50.2601121824, BIOS: Ubuntu 24.04.4 LTS, Microcode: Ubuntu 24.04.4 LTS, Kernel: 6.18-intel, Power Plan: Balanced Performance (6), Scaling Governor: powersave, Scaling Driver: intel_pstate, C-states: POLL: Enabled, C1_ACPI: Enabled, C2_ACPI: Enabled, C3_ACPI: Enabled, Graphics Driver Version (GPU): 26.01.36711.4, NPU Driver Version: 1.33.0.20260320, OpenVINO Version: E2E Tests: 2026.0.0Inference: 2025.3.0, DLStreamer Version: E2E Tests: 2026.0.0Inference: 2025.2.0" System 2: NVIDIA Jetson Orin Nano Engineering Reference Developer Kit Super (8GB), Test Date: Feb 2026, OEM / System: NVIDIA Jetson Orin Nano, CPU: 6-core Arm Cortex-A78AE v8.2 64-bit @ up to 1.73 GHz, Cores/Threads: 6-core, Module Power: 7-25W, GPU: NVIDIA Ampere architecture with 1024 NVIDIA® CUDA® cores and 32 Tensor cores , Accelerator: , Memory: 8GB 128-bit LPDDR5 @ 68.3 GB/s (2133 MHz), Storage: 512GB NVMe SSD, OS : Ubuntu 22.04.5 LTS, Kernel: 5.15.148-tegra, Power Plan: , Jetpack: 6.2.1, Deepstream: 7.1, CUDA: 12.6.68, TensorRT: 10.3.0.30, Jetson Clocks: schedutil (dynamic), NVP Modes: Currently: 0 (15W) Available: 0-15W, 1-25W, 2-MAXN_SUPER, 3-7W | Intel® Core™ 7 350 = 18 streams (1080p30) NVIDIA Jetson Orin™ Nano 8GB = 8 streams (1080p30) As measured by video streams at 1080p30, TDP = 15W. Medium AI Pipeline: Media Decode (1080p30 HEVC) + Preprocessing + Yolov5m_640x640 @ 10fps + Tracking + Resnet-50 @ 10 ips Reference workload available on Github https://github.com/open-edge-platform/edge-workloads-and-benchmarks | April 2026 |
| 300 | AI Inference | Intel® Core™ 7 350 is up to 1.9x faster image classification than NVIDIA Jetson Orin™ Nano | Intel® Core™ 7 350 processor | same as above | Intel® Core™ 7 350 GPU, mobilenet-v2, INT8, BS8 = 3849 inferences per second NVIDIA Jetson Orin™ Nano 8GB GPU, mobilenet-v2, INT8, BS8 = 2027 inferences per second TDP = 15W Performance varies by use, configuration and other factors. | April 2026 |
| 300 | AI Inference | Intel® Core™ 7 350 is up to 1.5x faster object detection than NVIDIA Jetson Orin™ Nano | Intel® Core™ 7 350 processor | same as above | Intel® Core™ 7 350 GPU, yolo_v5m, INT8, BS8 = 154 inferences per second NVIDIA Jetson Orin™ Nano 8GB, GPU yolo_v5m, INT8, BS8 = 103 inferences per second TDP = 15W Performance varies by use, configuration and other factors. | April 2026 |
| 300 | Edge Video Analytics Workload | Intel® Core™ 7 350 is up to 4.3x faster in end to end video analytics than Intel® Core™ 7 150U | Intel® Core™ 7 350 processor | System 1: Intel® Core™ 7 350, Test Date: April 2026, OEM / System: Intel Corporation Wildcat Lake Client Platform, 0.1, Model: Intel Corporation WCL DDR5 Embedded CRB, CPU: Intel(R) Core(TM) 7 350, Cores/Threads: 6, L3 Cache: 6 MB, TDP: 15W, Intel Turbo Boost: Enabled, Base Frequency: 1.5 GHz, Maximum Frequency: 4.8 GHz, Memory: 32GB (1x32GB DDR5 6400MT/s [6400MT/s]), Storage: 1x 465.8G Sabrent SB-RKT4P-500, OS : WCLPFWI1.R00.3515.D50.2601121824, BIOS: Ubuntu 24.04.4 LTS, Microcode: Ubuntu 24.04.4 LTS, Kernel: 6.18-intel, Power Plan: Balanced Performance (6), Scaling Governor: powersave, Scaling Driver: intel_pstate, C-states: POLL: Enabled, C1_ACPI: Enabled, C2_ACPI: Enabled, C3_ACPI: Enabled, Graphics Driver Version (GPU): 26.01.36711.4, NPU Driver Version: 1.33.0.20260320, OpenVINO Version: E2E Tests: 2026.0.0Inference: 2025.3.0, DLStreamer Version: E2E Tests: 2026.0.0Inference: 2025.2.0" System 2: Intel® Core™ 150U/250U, Test Date: December 2025, OEM / System: Intel Corporation Raptor Lake Client Platform, Model: -, CPU: Intel(R) Core(TM) 7 250U, Cores/Threads: 10, L3 Cache: 12 MiB, TDP: 15W, Intel Turbo Boost: Enabled, Base Frequency: 1.8GHz, Maximum Frequency: 1.8GHz, Memory: 32GB (2x16GB DDR5 4800MT/s [4800MT/s]), Storage: 1x 465.8G WDS500G3X0C-00SJG0, OS : RPLIPFI1.R00.5402.A02.2501230626, BIOS: Ubuntu 24.04.3 LTS, Microcode: RPLIPFI1.R00.5402.A02.2501230626, Kernel: 0x4128, Power Plan: 6.16.0-061600-generic, Scaling Governor: Balanced Performance (6), Scaling Driver: powersave, C-states: intel_pstate, Graphics Driver Version (GPU): POLL: Enabled, C1_ACPI: Enabled, C2_ACPI: Enabled, C3_ACPI: Enabled, NPU Driver Version: 25.35.35096.9, OpenVINO Version: 1.24.0, DLStreamer Version: 2025.3.0.0 | Intel® Core™ 7 350 = 18 streams (1080p30) Intel® Core™ 7 150U/250U = 4 streams (1080p30) As measured by video streams at 1080p30, TDP = 15W. Medium AI Pipeline: Media Decode (1080p30 HEVC) + Preprocessing + Yolov5m_640x640 @ 10fps + Tracking + Resnet-50 @ 10 ips Reference workload available on Github https://github.com/open-edge-platform/edge-workloads-and-benchmarks | April 2026 |
| 300 | AI Inference | The Intel® Core™ 7 350 is up to 2.5x faster image classification than Intel® Core™ 7 150U | Intel® Core™ 7 350 processor | same as above | Intel® Core™ 7 350 GPU, resnet-50, INT8, BS8 = 1016 inferences per second Intel® Core™ 7 150/250 GPU, resnet-50, INT8, BS8 = 412 inferences per second TDP = 15W As measured by inferences per second with resnet-50, TDP = 15W using built in GPU. Performance varies by use, configuration and other factors. | April 2026 |
| 300 | AI Inference | The Intel® Core™ 7 350 is up to 2.8x faster object detection than Intel® Core™ 7 150U | Intel® Core™ 7 350 processor | same as above | Intel® Core™ 7 350 GPU, yolo_v5m, INT8, BS8 = 154 inferences per second Intel® Core™ 7 150/250 GPU, yolo_v5m, INT8, BS8 = 54 inferences per second TDP = 15W Performance varies by use, configuration and other factors. | April 2026 |