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Batch Inference is now generally available on Runpod Serverless

NVIDIA

NVIDIA Nemotron 3.5 Super VL 120B A12B NVFP4

NVIDIA's 120B-parameter mixture-of-experts (12B active) open vision-language model, ready to serve on Runpod Serverless with vLLM or on a Pod.

Vision + language
Text generation
120B MoE · 12B active
See deploy options

NVIDIA Nemotron 3.5 Super VL 120B A12B NVFP4

Specifications

Provider
NVIDIA
Modality
Vision + language
Task
Text generation
Parameters
120B
Active parameters
12B
Context
Precision
NVFP4
Weights
68
License
openmdw-1.1
Released
2026-10-11
Endpoint ID
Weights on Hugging Face
nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4

Frequently asked questions

How do I deploy NVIDIA Nemotron 3.5 Super VL 120B A12B NVFP4 on Runpod?

Deploy the vLLM worker from the Runpod Hub as a Serverless endpoint and set MODEL_NAME to nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4. The endpoint is OpenAI-compatible and scales to zero when idle. You can also run vLLM on a Pod.

What GPU do I need to run NVIDIA Nemotron 3.5 Super VL 120B A12B NVFP4?

Start with RTX PRO 6000 (96 GB VRAM). The weights take about 68 GB; longer contexts and more concurrent requests need extra memory for the KV cache.

How much does NVIDIA Nemotron 3.5 Super VL 120B A12B NVFP4 cost on Runpod?

Serverless endpoints and Pods bill per second for the GPU you choose. A Serverless endpoint costs nothing while scaled to zero.

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No items found.
nvidia-nvidia-nemotron-3-5-super-vl-120b-a12b-nvfp4
nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4
Vision + language
2026-10-11 17:00
RTX PRO 6000