Mac16,9
Geekbench AI Score
5973
Single Precision Score
36892
Half Precision Score
50397
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| Upload Date | December 14 2025 04:23 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M4 Max |
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| 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 | 4.36 GHz |
| Cluster 1 | 12 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2183
405.9 IPS |
|
|
Image Classification (HP)
|
100% |
17326
3.22 KIPS |
|
|
Image Classification (Q)
|
97% |
21640
4.04 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2475
40.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
23095
374.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
31685
513.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
18327
21.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
123104
143.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
229245
268.7 IPS |
|
|
Object Detection (SP)
|
100% |
2686
213.1 IPS |
|
|
Object Detection (HP)
|
100% |
19379
1.54 KIPS |
|
|
Object Detection (Q)
|
91% |
24380
1.95 KIPS |
|
|
Face Detection (SP)
|
100% |
5249
62.4 IPS |
|
|
Face Detection (HP)
|
100% |
44167
524.8 IPS |
|
|
Face Detection (Q)
|
100% |
63006
748.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
8980
69.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
107535
828.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
177336
1.39 KIPS |
|
|
Style Transfer (SP)
|
100% |
31505
40.5 IPS |
|
|
Style Transfer (HP)
|
100% |
230946
296.9 IPS |
|
|
Style Transfer (Q)
|
96% |
317847
410.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6898
254.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
48505
1.79 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
82397
3.04 KIPS |
|
|
Text Classification (SP)
|
100% |
3240
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5607
7.48 KIPS |
|
|
Text Classification (Q)
|
93% |
5654
7.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
6550
112.8 IPS |
|
|
Machine Translation (HP)
|
100% |
16401
282.5 IPS |
|
|
Machine Translation (Q)
|
98% |
16673
288.1 IPS |
