Mac Studio (2023)
Geekbench ML Score
10111
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 06:13 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F79) |
| Model | Mac Studio (2023) |
| Model ID | Mac14,13 |
| Motherboard | Mac14,13 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.67 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 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 | 96.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6086
1.14 KIPS |
|
|
Image Classification (F16)
|
100% |
7177
1.34 KIPS |
|
|
Image Classification (I8)
|
99% |
8296
1.55 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2331
38.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1807
30.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1864
31.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
75361
91.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
77846
94.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
81889
99.2 IPS |
|
|
Object Detection (F32)
|
100% |
3690
275.5 IPS |
|
|
Object Detection (F16)
|
100% |
3992
298.0 IPS |
|
|
Object Detection (I8)
|
97% |
3705
276.6 IPS |
|
|
Face Detection (F32)
|
100% |
20825
247.6 IPS |
|
|
Face Detection (F16)
|
97% |
11233
133.6 IPS |
|
|
Face Detection (I8)
|
96% |
11228
133.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
30233
234.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
37582
291.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
38649
299.7 IPS |
|
|
Style Transfer (F32)
|
100% |
124737
164.1 IPS |
|
|
Style Transfer (F16)
|
100% |
137744
181.2 IPS |
|
|
Style Transfer (I8)
|
100% |
131581
173.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
19003
678.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18081
645.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17969
641.7 IPS |
|
|
Text Classification (F32)
|
100% |
528
758.1 IPS |
|
|
Text Classification (F16)
|
100% |
2658
3.82 KIPS |
|
|
Text Classification (I8)
|
96% |
2510
3.61 KIPS |
|
|
Machine Translation (F32)
|
100% |
1089
20.0 IPS |
|
|
Machine Translation (F16)
|
100% |
2726
50.2 IPS |
|
|
Machine Translation (I8)
|
99% |
1111
20.4 IPS |
