Mac17,3
Geekbench AI Score
5501
Single Precision Score
42887
Half Precision Score
60560
Quantized Score
Geekbench AI 1.7.0 for macOS AArch64
Result Information
| User | matta |
| Upload Date | March 19 2026 06:06 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M5 |
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E243) |
| Model | Mac17,3 |
| Model ID | Mac17,3 |
| Motherboard | Mac17,3 |
| CPU Information | |
|---|---|
| Name | Apple M5 |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M5 |
| Base Frequency | 4.46 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2211
411.1 IPS |
|
|
Image Classification (HP)
|
100% |
18744
3.49 KIPS |
|
|
Image Classification (Q)
|
97% |
26737
4.99 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2186
35.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
24869
403.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
34841
564.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
9690
11.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
178370
208.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
335805
393.6 IPS |
|
|
Object Detection (SP)
|
100% |
2734
216.9 IPS |
|
|
Object Detection (HP)
|
100% |
18673
1.48 KIPS |
|
|
Object Detection (Q)
|
89% |
28589
2.29 KIPS |
|
|
Face Detection (SP)
|
100% |
5108
60.7 IPS |
|
|
Face Detection (HP)
|
100% |
49457
587.7 IPS |
|
|
Face Detection (Q)
|
100% |
76230
905.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8789
67.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
112545
867.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
194361
1.52 KIPS |
|
|
Style Transfer (SP)
|
100% |
25473
32.7 IPS |
|
|
Style Transfer (HP)
|
100% |
274234
352.5 IPS |
|
|
Style Transfer (Q)
|
96% |
345955
446.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5663
209.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
66580
2.46 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
104531
3.86 KIPS |
|
|
Text Classification (SP)
|
99% |
5956
7.95 KIPS |
|
|
Text Classification (HP)
|
100% |
7349
9.81 KIPS |
|
|
Text Classification (Q)
|
93% |
7225
9.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
5146
88.6 IPS |
|
|
Machine Translation (HP)
|
100% |
18157
312.8 IPS |
|
|
Machine Translation (Q)
|
98% |
19167
331.2 IPS |
