Mac17,2
Geekbench AI Score
5332
Single Precision Score
41336
Half Precision Score
57985
Quantized Score
Geekbench AI 1.6.0 for macOS AArch64
Result Information
| User | Teva |
| Upload Date | January 24 2026 09:03 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M5 |
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| Model | Mac17,2 |
| Model ID | Mac17,2 |
| Motherboard | Mac17,2 |
| CPU Information | |
|---|---|
| Name | Apple M5 |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M5 |
| Base Frequency | 4.60 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2292
426.3 IPS |
|
|
Image Classification (HP)
|
100% |
18656
3.47 KIPS |
|
|
Image Classification (Q)
|
97% |
24183
4.51 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2424
39.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
23862
386.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
32679
529.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
11300
13.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
178154
207.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
334105
391.6 IPS |
|
|
Object Detection (SP)
|
100% |
2679
212.5 IPS |
|
|
Object Detection (HP)
|
100% |
18057
1.43 KIPS |
|
|
Object Detection (Q)
|
91% |
26374
2.11 KIPS |
|
|
Face Detection (SP)
|
100% |
4792
56.9 IPS |
|
|
Face Detection (HP)
|
100% |
46744
555.4 IPS |
|
|
Face Detection (Q)
|
100% |
67647
803.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
9090
70.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
110656
852.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
188833
1.48 KIPS |
|
|
Style Transfer (SP)
|
100% |
27153
34.9 IPS |
|
|
Style Transfer (HP)
|
100% |
270993
348.4 IPS |
|
|
Style Transfer (Q)
|
96% |
373705
482.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6015
222.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
63258
2.34 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
100293
3.70 KIPS |
|
|
Text Classification (SP)
|
100% |
3044
4.06 KIPS |
|
|
Text Classification (HP)
|
100% |
6506
8.68 KIPS |
|
|
Text Classification (Q)
|
93% |
6809
9.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
5103
87.9 IPS |
|
|
Machine Translation (HP)
|
100% |
17630
303.7 IPS |
|
|
Machine Translation (Q)
|
98% |
18931
327.1 IPS |
