Family Nemotron · 12.6B parameters

Nemotron Nano v2 VL 12B

12.6B enterprise VLM. Strong DocVQA/ChartQA. Professional document extraction.

🇺🇸 NVIDIA·License NVIDIA Open Model License·Context 125k tokens·Output May 2025·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • Vision + text in a 12B model
  • 128k context
  • NVIDIA Open Model License
Limitations to know
  • —Worse than Qwen3-VL 30B for complex vision
Architecture
Dense vision · 12.6B · Nemotron-Nano-v2 VL · 128k context
Training
NVIDIA Nemotron Nano v2 multimodal — text + images at 12B.
Ideal for
Enterprise OCRComplex documents

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$ollama run nemotron3-v2:12b
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
8 GB
Q5_K_M
Good quality/size compromise
10 GB
Q8_0
Nearly indistinguishable from FP16
14 GB
FP16
Full precision — server use
25 GB
Fallback CPU · If you don't have a GPU, allow 14 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Nemotron Nano v2 VL 12B?

To run Nemotron Nano v2 VL 12B locally with Q4 quantization, you need about 8 GB of VRAM. An option to compare: RTX 5060 Ti 16GB (ASUS Prime) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: RTX 5060 Ti 16GB (ASUS Prime)
AmazonSee price →

Affiliate links — commission possible at no extra cost to you; independent recommendation. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

On the go: Nemotron Nano v2 VL 12B also runs on a RTX laptop PC (16 GB of VRAM) →

This model in your private ChatGPT, without the cloud

Your private ChatGPT, free, on your own machine in an hour — LM Studio, Ollama, Open WebUI, your documents, no cloud.

  • Lifetime online access
  • PDF + files
  • Lifetime updates

03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~7t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~22t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~60t/s
RTX 4090, M4 Max, Radeon 7900