Support Matrix#

This page lists the supported models, their deployment profiles, and the verified hardware SKUs for NIM LLM.

Supported Models and Profiles#

Use the following sections to identify the supported deployment profiles for each model. Profile strings follow a naming convention described in Model Profiles and Selection.

Note

For supported hardware, refer to the Verified GPUs dropdown for each model or the GPU Compatibility section.

gpt-oss-120b#

The following table lists the supported profile configurations for gpt-oss-120b:

Precision	TP1	TP2	TP4	TP8
MXFP4	`vllm-mxfp4-tp1-pp1`	`vllm-mxfp4-tp2-pp1`	`vllm-mxfp4-tp4-pp1`	`vllm-mxfp4-tp8-pp1`
MXFP4 + LoRA	`vllm-mxfp4-tp1-pp1-lora`	`vllm-mxfp4-tp2-pp1-lora`	`vllm-mxfp4-tp4-pp1-lora`	`vllm-mxfp4-tp8-pp1-lora`

gpt-oss-20b#

The following table lists the supported profile configurations for gpt-oss-20b:

Precision	TP1	TP2	TP4	TP8
MXFP4	`vllm-mxfp4-tp1-pp1`	`vllm-mxfp4-tp2-pp1`	`vllm-mxfp4-tp4-pp1`	`vllm-mxfp4-tp8-pp1`
MXFP4 + LoRA	`vllm-mxfp4-tp1-pp1-lora`	`vllm-mxfp4-tp2-pp1-lora`	`vllm-mxfp4-tp4-pp1-lora`	`vllm-mxfp4-tp8-pp1-lora`

llama-3.1-70b-instruct#

The following table lists the supported profile configurations for llama-3.1-70b-instruct:

Precision	TP1	TP2	TP4	TP8
BF16	`vllm-bf16-tp1-pp1`	`vllm-bf16-tp2-pp1`	`vllm-bf16-tp4-pp1`	`vllm-bf16-tp8-pp1`
BF16 + LoRA	`vllm-bf16-tp1-pp1-lora`	`vllm-bf16-tp2-pp1-lora`	`vllm-bf16-tp4-pp1-lora`	`vllm-bf16-tp8-pp1-lora`
FP8	`vllm-fp8-tp1-pp1`	`vllm-fp8-tp2-pp1`	`vllm-fp8-tp4-pp1`	`vllm-fp8-tp8-pp1`
FP8 + LoRA	`vllm-fp8-tp1-pp1-lora`	`vllm-fp8-tp2-pp1-lora`	`vllm-fp8-tp4-pp1-lora`	`vllm-fp8-tp8-pp1-lora`
NVFP4	`vllm-nvfp4-tp1-pp1`	`vllm-nvfp4-tp2-pp1`	`vllm-nvfp4-tp4-pp1`	`vllm-nvfp4-tp8-pp1`
NVFP4 + LoRA	`vllm-nvfp4-tp1-pp1-lora`	`vllm-nvfp4-tp2-pp1-lora`	`vllm-nvfp4-tp4-pp1-lora`	`vllm-nvfp4-tp8-pp1-lora`

llama-3.1-8b-instruct#

The following table lists the supported profile configurations for llama-3.1-8b-instruct:

Precision	TP1
BF16	`vllm-bf16-tp1-pp1`
BF16 + LoRA	`vllm-bf16-tp1-pp1-lora`
FP8	`vllm-fp8-tp1-pp1`
FP8 + LoRA	`vllm-fp8-tp1-pp1-lora`
NVFP4	`vllm-nvfp4-tp1-pp1`
NVFP4 + LoRA	`vllm-nvfp4-tp1-pp1-lora`

llama-3.3-70b-instruct#

The following table lists the supported profile configurations for llama-3.3-70b-instruct:

Precision	TP1	TP2	TP4	TP8
BF16	`vllm-bf16-tp1-pp1`	`vllm-bf16-tp2-pp1`	`vllm-bf16-tp4-pp1`	`vllm-bf16-tp8-pp1`
BF16 + LoRA	`vllm-bf16-tp1-pp1-lora`	`vllm-bf16-tp2-pp1-lora`	`vllm-bf16-tp4-pp1-lora`	`vllm-bf16-tp8-pp1-lora`
FP8	`vllm-fp8-tp1-pp1`	`vllm-fp8-tp2-pp1`	`vllm-fp8-tp4-pp1`	`vllm-fp8-tp8-pp1`
FP8 + LoRA	`vllm-fp8-tp1-pp1-lora`	`vllm-fp8-tp2-pp1-lora`	`vllm-fp8-tp4-pp1-lora`	`vllm-fp8-tp8-pp1-lora`
NVFP4	`vllm-nvfp4-tp1-pp1`	`vllm-nvfp4-tp2-pp1`	`vllm-nvfp4-tp4-pp1`	`vllm-nvfp4-tp8-pp1`
NVFP4 + LoRA	–	`vllm-nvfp4-tp2-pp1-lora`	`vllm-nvfp4-tp4-pp1-lora`	`vllm-nvfp4-tp8-pp1-lora`

llama-3.3-nemotron-super-49b-v1.5#

The following table lists the supported profile configurations for llama-3.3-nemotron-super-49b-v1.5:

Precision	TP1	TP2	TP4	TP8
BF16	`vllm-bf16-tp1-pp1`	`vllm-bf16-tp2-pp1`	`vllm-bf16-tp4-pp1`	`vllm-bf16-tp8-pp1`
BF16 + LoRA	`vllm-bf16-tp1-pp1-lora`	`vllm-bf16-tp2-pp1-lora`	`vllm-bf16-tp4-pp1-lora`	`vllm-bf16-tp8-pp1-lora`
FP8	`vllm-fp8-tp1-pp1`	`vllm-fp8-tp2-pp1`	`vllm-fp8-tp4-pp1`	`vllm-fp8-tp8-pp1`
FP8 + LoRA	`vllm-fp8-tp1-pp1-lora`	`vllm-fp8-tp2-pp1-lora`	`vllm-fp8-tp4-pp1-lora`	`vllm-fp8-tp8-pp1-lora`
NVFP4	`vllm-nvfp4-tp1-pp1`	`vllm-nvfp4-tp2-pp1`	`vllm-nvfp4-tp4-pp1`	`vllm-nvfp4-tp8-pp1`
NVFP4 + LoRA	`vllm-nvfp4-tp1-pp1-lora`	`vllm-nvfp4-tp2-pp1-lora`	`vllm-nvfp4-tp4-pp1-lora`	`vllm-nvfp4-tp8-pp1-lora`

nemotron-3-nano#

The following table lists the supported profile configurations for nemotron-3-nano:

Precision	TP1	TP2	TP4	TP8
BF16	`vllm-bf16-tp1-pp1`	`vllm-bf16-tp2-pp1`	`vllm-bf16-tp4-pp1`	`vllm-bf16-tp8-pp1`
BF16 + LoRA	`vllm-bf16-tp1-pp1-lora`	`vllm-bf16-tp2-pp1-lora`	`vllm-bf16-tp4-pp1-lora`	`vllm-bf16-tp8-pp1-lora`
FP8	`vllm-fp8-tp1-pp1`	`vllm-fp8-tp2-pp1`	`vllm-fp8-tp4-pp1`	`vllm-fp8-tp8-pp1`
FP8 + LoRA	`vllm-fp8-tp1-pp1-lora`	`vllm-fp8-tp2-pp1-lora`	`vllm-fp8-tp4-pp1-lora`	`vllm-fp8-tp8-pp1-lora`
NVFP4	`vllm-nvfp4-tp1-pp1`	`vllm-nvfp4-tp2-pp1`	`vllm-nvfp4-tp4-pp1`	`vllm-nvfp4-tp8-pp1`
NVFP4 + LoRA	`vllm-nvfp4-tp1-pp1-lora`	`vllm-nvfp4-tp2-pp1-lora`	`vllm-nvfp4-tp4-pp1-lora`	`vllm-nvfp4-tp8-pp1-lora`

starcoder2-7b#

The following table lists the supported profile configurations for starcoder2-7b:

Precision	TP1	TP2
BF16	`vllm-bf16-tp1-pp1`	`vllm-bf16-tp2-pp1`

Model-Free NIM#

The following models are tested and validated for model-free NIM:

gpt-oss-20b
apriel-nemotron
codestral

While not explicitly validated, the model-free NIM can be used with any model supported by the underlying backend (vLLM) version. Refer to Model-Free NIM for deployment details.

GPU Compatibility#

Use the following dropdowns to determine which models are supported on a given GPU:

1.x NIM LLM Models#

For more information on version 1.x NIMs, refer to the 1.15 version of the NIM LLM Supported Models page.

Show 1.x models

Model (Hardware Requirements)	Organization/Model ID (Catalog Page)
DeepSeek-V3.1-Terminus	`deepseek-ai/deepseek-v3.1-terminus`
DeepSeek-V3.2-Exp	`deepseek-ai/deepseek-v32-exp-nim`
GLM-5	`zai-org/glm-5`
Llama-3.1-Nemotron-Nano-8B-Healthcare-Text2sql-v1.0	`nvidia/llama-3.1-nemotron-nano-8b-healthcare-text2sql-v1.0`
Llama-3.3-Nemotron-Super-49B-Healthcare-Text2sql-v1.0	`nvidia/llama-3.3-nemotron-super-49b-healthcare-text2sql-v1.0`
MiniMax-M2.5	`minimax-ai/minimax-m25`
NVIDIA-Nemotron-Nano-9B-v2-DGX-Spark	`nvidia/nvidia-nemotron-nano-9b-v2-dgx-spark`
Nemotron-3-Super-120B-A12B	`nvidia/nemotron-3-super-120b-a12b`
Qwen3-Coder-Next	`qwen/qwen3-coder-next`
Qwen3-Next-80B-A3B-Instruct	`qwen/qwen3-next-80b-a3b-instruct`
Qwen3 Next 80B A3B Thinking	`qwen/qwen3-next-80b-a3b-thinking`
Qwen3-32B	`qwen/qwen3-32b`
Qwen3-32B NIM for DGX Spark	`qwen/qwen3-32b-dgx-spark`
Riva-Translate-4b-Instruct-v1.1	`nvidia/riva-translate-4b-instruct-v1.1`