Mac16,9
Geekbench AI Score
6014
Single Precision Score
36421
Half Precision Score
49509
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| Upload Date | November 13 2025 12:41 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M4 Max |
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B78) |
| 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 | 4.51 GHz |
| Cluster 1 | 12 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2206
410.3 IPS |
|
|
Image Classification (HP)
|
100% |
16944
3.15 KIPS |
|
|
Image Classification (Q)
|
97% |
21331
3.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2469
40.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
22998
372.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
31995
518.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
18505
21.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
122283
142.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
228676
268.0 IPS |
|
|
Object Detection (SP)
|
100% |
2701
214.2 IPS |
|
|
Object Detection (HP)
|
100% |
19073
1.51 KIPS |
|
|
Object Detection (Q)
|
91% |
23456
1.87 KIPS |
|
|
Face Detection (SP)
|
100% |
5329
63.3 IPS |
|
|
Face Detection (HP)
|
100% |
44079
523.8 IPS |
|
|
Face Detection (Q)
|
100% |
62734
745.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
9058
69.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
104465
804.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
174929
1.37 KIPS |
|
|
Style Transfer (SP)
|
100% |
31754
40.8 IPS |
|
|
Style Transfer (HP)
|
100% |
232330
298.7 IPS |
|
|
Style Transfer (Q)
|
96% |
319360
412.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7059
260.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
47384
1.75 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
77568
2.86 KIPS |
|
|
Text Classification (SP)
|
100% |
3219
4.30 KIPS |
|
|
Text Classification (HP)
|
99% |
5607
7.48 KIPS |
|
|
Text Classification (Q)
|
93% |
5590
7.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
6532
112.5 IPS |
|
|
Machine Translation (HP)
|
100% |
15900
273.9 IPS |
|
|
Machine Translation (Q)
|
98% |
15907
274.9 IPS |
