AI hardware re-ranked by training-category score — the throughput profile that matters when the workload is model training rather than inference or raw compute. GT and the other two category scores stay visible for context. Results: 26Q3.
| # | Device Accelerator / GPU | GT Global Score | Training Category | Inference Category | Compute Category | Platform OS |
|---|---|---|---|---|---|---|
| 1 |
1306.35
|
1089.67
|
2224.55
|
611.10
|
Native Linux | |
| 2 |
1277.42
|
1080.48
|
2105.93
|
624.58
|
Native Linux | |
| 3 |
1044.99
|
811.98
|
1914.61
|
480.83
|
Native Linux | |
| 4 |
986.72
|
727.23
|
1304.04
|
1023.28
|
Native Linux | |
| 5 |
939.45
|
709.35
|
1678.11
|
487.13
|
Native Linux | |
| 6 |
692.67
|
588.50
|
1123.94
|
347.75
|
Native Linux | |
| 7 |
718.86
|
587.80
|
1201.04
|
366.56
|
Native Linux | |
| 8 |
597.49
|
515.26
|
985.84
|
279.64
|
Native Linux | |
| 9 |
440.29
|
415.55
|
660.97
|
210.04
|
Native Linux | |
| 10 |
403.38
|
387.30
|
584.07
|
201.12
|
Native Linux | |
| 11 |
450.05
|
335.94
|
659.37
|
367.89
|
Native Linux | |
| 12 |
395.82
|
316.04
|
528.12
|
344.33
|
Native Linux | |
| 13 |
202.73
|
207.55
|
294.13
|
87.37
|
Native Linux | |
| 14 |
160.52
|
163.70
|
240.49
|
64.77
|
Native Linux | |
| 15 |
158.79
|
157.40
|
231.75
|
72.52
|
WSL | |
| 16 |
146.10
|
133.08
|
239.43
|
61.68
|
Native Linux | |
| 17 |
74.55
|
60.71
|
100.85
|
60.59
|
WSL | |
| 18 |
76.32
|
37.28
|
122.73
|
112.62
|
Native Linux | |
| 19 |
5.20
|
8.58
|
2.69
|
6.32
|
Native Linux | |
| 20 |
6.35
|
8.52
|
5.78
|
4.19
|
WSL | |
| 21 |
7.87
|
6.69
|
9.05
|
8.30
|
Native Linux | |
| 22 |
0.34
|
0.70
|
0.34
|
0.07
|
WSL | |
| 23 |
0.30
|
0.20
|
0.17
|
1.59
|
WSL |
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Results: 26Q3 · ranked by training-category score, higher is better. GT (Global Score) is LynxBenchAI's overall crown; this view answers "which hardware leads specifically on training," not "which hardware wins overall." Bars are scaled to each column's own leader, not a shared ceiling -- compare bars down a column, not across.