Mac Studio (2023)
Geekbench ML Score
9751
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | April 23 2024 08:05 AM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| 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 | 3.48 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5550
1.04 KIPS |
|
|
Image Classification (F16)
|
100% |
7118
1.33 KIPS |
|
|
Image Classification (I8)
|
99% |
7911
1.48 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2277
38.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1875
31.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1858
31.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
56876
68.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
80299
97.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
82255
99.6 IPS |
|
|
Object Detection (F32)
|
100% |
4042
301.7 IPS |
|
|
Object Detection (F16)
|
100% |
3666
273.7 IPS |
|
|
Object Detection (I8)
|
97% |
3929
293.4 IPS |
|
|
Face Detection (F32)
|
100% |
19257
229.0 IPS |
|
|
Face Detection (F16)
|
97% |
11154
132.6 IPS |
|
|
Face Detection (I8)
|
96% |
11085
131.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
27122
210.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
36060
279.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
37667
292.1 IPS |
|
|
Style Transfer (F32)
|
100% |
106410
140.0 IPS |
|
|
Style Transfer (F16)
|
100% |
132117
173.8 IPS |
|
|
Style Transfer (I8)
|
100% |
135252
177.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
18101
646.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17586
628.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16273
581.2 IPS |
|
|
Text Classification (F32)
|
100% |
471
676.4 IPS |
|
|
Text Classification (F16)
|
100% |
2838
4.08 KIPS |
|
|
Text Classification (I8)
|
96% |
2763
3.97 KIPS |
|
|
Machine Translation (F32)
|
100% |
1019
18.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2558
47.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1041
19.2 IPS |
