NIM Containers – Resource bundles¶

Below is a quick-look bundle-sizing guide for the three managed-Kubernetes platforms. Each table shows, per cloud, how our standard bundle labels (M, L, XL, 2 XL, 3 XL, 4 XL) map to GPU nodes and the aggregate FP16 throughput and memory you can expect.

See also NIM validation on GPU bundles

EKS (AWS):

バンドル	GPU Type	GPU Count	FP16 TFLOPS	VRAM (GB)	Total FP16 TFLOPS	Total VRAM (GB)	RAM (GB)
S	T4	1	65	16	65	16	10
M	A10	1	125	24	125	24	32
L	L40S	1	181	48	181	48	32
XL	A10	4	125	24	500	96	192
XXL	L40S	4	181	48	724	192	384
3XL	L40S	8	181	48	1448	384	1536
4XL	A100 SXM	8	312	80	2496	640	1152

AKS (Azure):

バンドル	GPU Type	GPU Count	FP16 TFLOPS	VRAM (GB)	Total FP16 TFLOPS	Total VRAM (GB)	RAM (GB)
M	A10	1	125	24	125	24	440
L	A10	2	125	24	250	48	880
XL	A100 PCIe	1	312	80	312	80	220
2XL	A100 PCIe	2	312	80	624	160	440
3XL	A100 PCIe	4	312	80	1248	320	900
4XL	A100 SXM	8	312	80	2496	640	1900

OCP (Oracle):

バンドル	GPU Type	GPU Count	FP16 TFLOPS	VRAM (GB)	Total FP16 TFLOPS	Total VRAM (GB)	RAM (GB)
XL	A100 SXM	1	312	80	312	80	80
2XL	A100 SXM	2	312	80	624	160	160
3XL	A100 SXM	4	312	80	1248	320	320
4XL	A100 SXM	8	312	80	2496	640	640

OKE H100 (Oracle):

バンドル	GPU Type	GPU Count	FP16 TFLOPS	VRAM (GB)	Total FP16 TFLOPS	Total VRAM (GB)	RAM (GB)
XL	H100 SXM	1	1000	80	1000	80	80
2XL	H100 SXM	2	1000	80	2000	160	160
3XL	H100 SXM	4	1000	80	4000	320	320
4XL	H100 SXM	8	1000	80	8000	640	640