Mac16,9
Geekbench AI Score
5968
Single Precision Score
36176
Half Precision Score
48872
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| Upload Date | March 07 2025 09:11 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M4 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D2059) |
| Model | Mac16,9 |
| Model ID | Mac16,9 |
| Motherboard | Mac16,9 |
| CPU Information | |
|---|---|
| Name | Apple M4 Max |
| Topology | 1 Processor, 16 Cores |
| Identifier | Apple M4 Max |
| Base Frequency | 4.50 GHz |
| Cluster 1 | 12 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2129
395.9 IPS |
|
|
Image Classification (HP)
|
100% |
16873
3.14 KIPS |
|
|
Image Classification (Q)
|
97% |
21814
4.07 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2550
41.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
22502
364.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
31320
507.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
19173
22.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
123070
143.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
230410
270.1 IPS |
|
|
Object Detection (SP)
|
100% |
2589
205.3 IPS |
|
|
Object Detection (HP)
|
100% |
18772
1.49 KIPS |
|
|
Object Detection (Q)
|
91% |
22930
1.83 KIPS |
|
|
Face Detection (SP)
|
100% |
4823
57.3 IPS |
|
|
Face Detection (HP)
|
100% |
44090
523.9 IPS |
|
|
Face Detection (Q)
|
100% |
63498
754.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
9143
70.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
108920
839.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
175457
1.37 KIPS |
|
|
Style Transfer (SP)
|
100% |
37476
48.2 IPS |
|
|
Style Transfer (HP)
|
100% |
233090
299.6 IPS |
|
|
Style Transfer (Q)
|
96% |
296997
383.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7221
266.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
44865
1.66 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
76844
2.84 KIPS |
|
|
Text Classification (SP)
|
100% |
2949
3.94 KIPS |
|
|
Text Classification (HP)
|
100% |
5469
7.30 KIPS |
|
|
Text Classification (Q)
|
93% |
5302
7.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
6046
104.1 IPS |
|
|
Machine Translation (HP)
|
100% |
15937
274.5 IPS |
|
|
Machine Translation (Q)
|
98% |
15975
276.1 IPS |
