Mac Studio (2023)
Geekbench ML Score
9146
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 20 2024 08:41 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.2.1 (Build 23C71) |
| 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% |
1097
205.3 IPS |
|
|
Image Classification (F16)
|
100% |
7192
1.35 KIPS |
|
|
Image Classification (I8)
|
99% |
7391
1.38 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2321
38.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1721
28.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1730
28.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
95756
116.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
77955
94.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
82471
99.9 IPS |
|
|
Object Detection (F32)
|
100% |
3653
272.7 IPS |
|
|
Object Detection (F16)
|
100% |
4719
352.3 IPS |
|
|
Object Detection (I8)
|
97% |
3670
274.0 IPS |
|
|
Face Detection (F32)
|
100% |
23813
283.1 IPS |
|
|
Face Detection (F16)
|
97% |
29259
347.9 IPS |
|
|
Face Detection (I8)
|
96% |
29348
349.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
29407
228.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
42064
326.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
38011
294.8 IPS |
|
|
Style Transfer (F32)
|
100% |
168876
222.1 IPS |
|
|
Style Transfer (F16)
|
100% |
132578
174.4 IPS |
|
|
Style Transfer (I8)
|
100% |
134459
176.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
18902
675.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18376
656.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18332
654.7 IPS |
|
|
Text Classification (F32)
|
100% |
391
561.7 IPS |
|
|
Text Classification (F16)
|
100% |
716
1.03 KIPS |
|
|
Text Classification (I8)
|
96% |
657
944.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1080
19.9 IPS |
|
|
Machine Translation (F16)
|
99% |
1130
20.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1059
19.5 IPS |
