Mac Studio (2023)
Geekbench ML Score
8579
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 21 2024 12:59 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | Mac Studio (2023) |
| Model ID | Mac14,14 |
| Motherboard | Mac14,14 |
| CPU Information | |
|---|---|
| Name | Apple M2 Ultra |
| Topology | 1 Processor, 24 Cores |
| Identifier | Apple M2 Ultra |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 16 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1091
204.2 IPS |
|
|
Image Classification (F16)
|
100% |
7188
1.35 KIPS |
|
|
Image Classification (I8)
|
99% |
7588
1.42 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2207
36.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1694
28.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1680
28.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
94975
115.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
79741
96.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
81567
98.8 IPS |
|
|
Object Detection (F32)
|
100% |
3742
279.3 IPS |
|
|
Object Detection (F16)
|
100% |
3406
254.3 IPS |
|
|
Object Detection (I8)
|
97% |
3724
278.0 IPS |
|
|
Face Detection (F32)
|
100% |
22264
264.7 IPS |
|
|
Face Detection (F16)
|
97% |
11054
131.4 IPS |
|
|
Face Detection (I8)
|
96% |
11130
132.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
30766
238.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
40702
315.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
38220
296.4 IPS |
|
|
Style Transfer (F32)
|
100% |
170024
223.7 IPS |
|
|
Style Transfer (F16)
|
100% |
132076
173.7 IPS |
|
|
Style Transfer (I8)
|
100% |
131649
173.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
18766
670.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18139
647.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17568
627.4 IPS |
|
|
Text Classification (F32)
|
100% |
807
1.16 KIPS |
|
|
Text Classification (F16)
|
100% |
649
933.1 IPS |
|
|
Text Classification (I8)
|
96% |
648
931.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1036
19.1 IPS |
|
|
Machine Translation (F16)
|
99% |
1095
20.2 IPS |
|
|
Machine Translation (I8)
|
99% |
1032
19.0 IPS |
