Support Matrix#

Hardware#

Unless specified otherwise, NVIDIA NIM for vision language models (VLMs) should, but are not guaranteed to, run on any NVIDIA GPU, provided the GPU has sufficient memory. They can also run on multiple homogeneous NVIDIA GPUs with sufficient aggregate memory and a CUDA compute capability of >= 7.0 (8.0 for bfloat16) unless otherwise specified. For more information, refer to Supported Models.

NVIDIA NIM for VLMs does not support NVIDIA Virtual GPU (vGPU) environments.

For information on the supported operating systems, drivers, and software, refer to the About Get Started page.

Supported Models#

Qwen3.5-397B-A17B#

Latest supported release tag: 2.0.4-variant

The following section lists the supported configurations for qwen/qwen3.5-397b-a17b (NGC catalog page).

Generic Configuration#

NIM for VLMs offers competitive performance through a custom vLLM backend. Any NVIDIA GPU with sufficient memory should be able to run this model, though this is not guaranteed.

The GPU Memory and Disk Space values are in GB. The disk space values for LoRA-enabled profiles do not include the LoRA model weights.

GPU

GPU Memory

Precision

LoRA

# of GPUs

Disk Space

B300

288

NVFP4

Yes

2,4,8

240

B300

288

FP8

Yes

4,8

380

B300

288

BF16

Yes

4,8

760

B300

288

NVFP4

No

2,4,8

240

B300

288

FP8

No

2,4,8

380

B300

288

BF16

No

4,8

760

GB300

288

NVFP4

Yes

2,4

240

GB300

288

FP8

Yes

4

380

GB300

288

BF16

Yes

4

760

GB300

288

NVFP4

No

2,4

240

GB300

288

FP8

No

2,4

380

GB300

288

BF16

No

4

760

B200

192

NVFP4

Yes

4,8

240

B200

192

FP8

Yes

8

380

B200

192

NVFP4

No

2,4,8

240

B200

192

FP8

No

4,8

380

B200

192

BF16

No

8

760

GB200

192

NVFP4

Yes

4

240

GB200

192

NVFP4

No

2,4

240

GB200

192

FP8

No

4

380

H200 SXM

141

FP8

Yes

8

380

H200 SXM

141

FP8

No

4,8

380

H200 SXM

141

BF16

No

8

760

H200 NVL

141

FP8

Yes

8

380

H200 NVL

141

FP8

No

4,8

380

H200 NVL

141

BF16

No

8

760

H100 SXM

80

FP8

No

8

380

H100 NVL

94

FP8

No

8

380

RTX PRO 6000 BSE

96

NVFP4

Yes

8

240

RTX PRO 6000 BSE

96

FP8

No

8

380

RTX PRO 6000 BSE

96

NVFP4

No

4,8

240

Qwen3.5-122B-A10B#

Latest supported release tag: 2.0.4-variant

The following section lists the supported configurations for qwen/qwen3.5-122b-a10b (NGC catalog page).

Generic Configuration#

NIM for VLMs offers competitive performance through a custom vLLM backend. Any NVIDIA GPU with sufficient memory, or multiple homogeneous NVIDIA GPUs with sufficient aggregate memory, should be able to run this model, though this is not guaranteed. It requires compute capability >= 9.0.

The GPU Memory and Disk Space values are in GB. The disk space values for LoRA-enabled profiles do not include the LoRA model weights.

GPU

GPU Memory

Precision

LoRA

# of GPUs

Disk Space

B300

288

BF16

Yes

2,4,8

240

B300

288

FP8

Yes

1,2,4,8

120

B300

288

NVFP4

Yes

1,2

80

B300

288

BF16

No

2,4,8

240

B300

288

FP8

No

1,2,4,8

120

B300

288

NVFP4

No

1,2

80

GB300

288

BF16

Yes

2,4

240

GB300

288

FP8

Yes

1,2,4

120

GB300

288

NVFP4

Yes

1,2

80

GB300

288

BF16

No

2,4

240

GB300

288

FP8

No

1,2,4

120

GB300

288

NVFP4

No

1,2

80

B200

192

BF16

Yes

2,4,8

240

B200

192

FP8

Yes

1,2,4,8

120

B200

192

NVFP4

Yes

1,2

80

B200

192

BF16

No

2,4,8

240

B200

192

FP8

No

1,2,4,8

120

B200

192

NVFP4

No

1,2

80

GB200

192

BF16

Yes

2,4

240

GB200

192

FP8

Yes

1,2,4

120

GB200

192

NVFP4

Yes

1,2

80

GB200

192

BF16

No

2,4

240

GB200

192

FP8

No

1,2,4

120

GB200

192

NVFP4

No

1,2

80

H200 SXM

141

BF16

Yes

4,8

240

H200 SXM

141

FP8

Yes

2,4,8

120

H200 SXM

141

BF16

No

4,8

240

H200 SXM

141

FP8

No

2,4,8

120

H200 NVL

141

BF16

Yes

4,8

240

H200 NVL

141

FP8

Yes

2,4,8

120

H200 NVL

141

BF16

No

4,8

240

H200 NVL

141

FP8

No

2,4,8

120

GH200

141

FP8

Yes

2

120

GH200

141

FP8

No

2

120

H100 SXM

80

BF16

Yes

8

240

H100 SXM

80

FP8

Yes

4,8

120

H100 SXM

80

BF16

No

8

240

H100 SXM

80

FP8

No

4,8

120

H100 NVL

94

BF16

Yes

4,8

240

H100 NVL

94

FP8

Yes

2,4,8

120

H100 NVL

94

BF16

No

4,8

240

H100 NVL

94

FP8

No

2,4,8

120

A100 SXM

80

BF16

Yes

8

240

A100 SXM

80

BF16

No

8

240

GB10

128

NVFP4

No

1

80

L40S

48

BF16

Yes

8

240

L40S

48

FP8

Yes

8

120

L40S

48

BF16

No

8

240

L40S

48

FP8

No

8

120

RTX PRO 4500 BSE

48

FP8

Yes

8

120

RTX PRO 4500 BSE

48

FP8

No

8

120

RTX PRO 6000 BSE

96

BF16

Yes

4,8

240

RTX PRO 6000 BSE

96

FP8

Yes

2,4,8

120

RTX PRO 6000 BSE

96

NVFP4

Yes

2

80

RTX PRO 6000 BSE

96

BF16

No

4,8

240

RTX PRO 6000 BSE

96

FP8

No

2,4,8

120

RTX PRO 6000 BSE

96

NVFP4

No

2

80

Kimi-K2.6#

Latest supported release tag: 2.0.4-variant

The following section lists the supported configurations for moonshotai/kimi-k2.6 (NGC catalog page).

Generic Configuration#

Kimi-K2.6 is a ~1T-parameter MoE VLM. It ships as INT4 only, with two tensor-parallel profiles selected automatically based on per-GPU memory.

The GPU Memory column is per-GPU HBM in GB; the Disk Space column is the NGC artifact size needed in the NIM cache (one-time download on first launch), in GB.

GPU

GPU Memory

Precision

# of GPUs

Disk Space

H200

141

INT4

8

600

H200 NVL

141

INT4

8

600

B200

192

INT4

8

600

B300 SXM (288 GB)

288

INT4

4 or 8

600

GB300 NVL

288

INT4

4

600

Nemotron-3-Nano-Omni-30B-A3B-Reasoning#

Latest supported release tag: 2.0.4-variant

The following section lists the supported configurations for nvidia/nemotron-3-nano-omni-30b-a3b-reasoning (NGC catalog page).

Generic Configuration#

NIM for VLMs offers competitive performance through a custom vLLM backend. Any NVIDIA GPU with sufficient memory should be able to run this model, though this is not guaranteed.

The GPU Memory and Disk Space values are in GB.

GPU

GPU Memory

Precision

# of GPUs

Disk Space

A100 SXM4 (40 GB)

40

BF16

2

80

A100 SXM4 (80 GB)

80

BF16

1 or 2

80

L40S

48

BF16

2

80

L40S

48

FP8

1

50

H100 SXM (80 GB)

80

BF16

1 or 2

80

H100 SXM (80 GB)

80

FP8

1

50

H100 NVL

94

BF16

1 or 2

80

H100 NVL

94

FP8

1

50

H200

141

BF16

1 or 2

80

H200

141

FP8

1

50

H200 NVL

141

BF16

1 or 2

80

H200 NVL

141

FP8

1

50

GH200 (144 GB)

144

BF16

1 or 2

80

GH200 (144 GB)

144

FP8

1

50

GH200 (480 GB)

480

BF16

1

80

GH200 (480 GB)

480

FP8

1

50

B200

192

BF16

1 or 2

80

B200

192

FP8

1

50

B200

192

NVFP4

1

40

GB200 NVL

192

BF16

1 or 2

80

GB200 NVL

192

FP8

1

50

GB200 NVL

192

NVFP4

1

40

RTX PRO 4500 Blackwell SE

32

NVFP4

1

40

RTX PRO 6000 Blackwell SE

96

BF16

1 or 2

80

RTX PRO 6000 Blackwell SE

96

FP8

1

50

RTX PRO 6000 Blackwell SE

96

NVFP4

1

40

B300 SXM6 (288 GB)

288

BF16

1 or 2

80

B300 SXM6 (288 GB)

288

FP8

1

50

B300 SXM6 (288 GB)

288

NVFP4

1

40

GB300 NVL

288

BF16

1 or 2

80

GB300 NVL

288

FP8

1

50

GB300 NVL

288

NVFP4

1

40

Supported codecs and video formats#

This model supports the following codecs and video formats for an input video:

  • Supported codecs: H264, H265, VP8, VP9

  • Supported video formats: MP4, FLV, 3GP