How much VRAM does Nemotron-Nano 9B v2 need?

Nemotron-Nano 9B v2 requires approximately 0.0 GB VRAM at Q4_K_M quantization with 1K context and 10% overhead. At Q8_0 it needs ~0.0 GB, and at FP16 ~0.0 GB. Use the PCPARTGUIDE VRAM Calculator for exact requirements at any context length and overhead setting.

Can I run Nemotron-Nano 9B v2 on a consumer GPU?

Yes, Nemotron-Nano 9B v2 can run on consumer GPUs. At Q4_K_M quantization with moderate context length, it fits on a 12 GB GPU. For best performance, use a 16 GB or larger GPU with at least 8 GB VRAM for reasonable context lengths.

What is Nemotron-Nano 9B v2's context window?

Nemotron-Nano 9B v2 supports a maximum context window of 131,072 tokens. The default context is 8,192 tokens. Larger contexts require proportionally more VRAM for the KV cache — use the VRAM Calculator to estimate exact requirements at your target context length.

What quantization level should I use for Nemotron-Nano 9B v2?

For Nemotron-Nano 9B v2, Q4_K_M is the recommended quantization — it provides an excellent quality-to-VRAM ratio at ~0.0 GB. Q8_0 offers slightly better quality at ~2× the VRAM. Q4_K_M is the sweet spot for most users.

How does Nemotron-Nano 9B v2 compare to similar models?

Nemotron-Nano 9B v2 is a 9.0B Dense model from the Nvidia family. Browse other Nvidia models on the PCPARTGUIDE directory for comparable alternatives with different parameter counts and VRAM requirements. Use the Model Transparency scores to assess documentation quality and reproducibility.

NvidiaDenseNVIDIA Open Model License

Nemotron-Nano 9B v2

9.0B

Parameters

128K

Max Context

Dense

Architecture

Nov 18, 2025

Released

Text

Modality

About Nemotron-Nano 9B v2

Nemotron-Nano 9B v2 is NVIDIA's unified reasoning/non-reasoning model. It can toggle between fast standard generation and extended chain-of-thought reasoning, making it versatile for both interactive chat and structured problem-solving. At 9B parameters with 128K context and competitive benchmark scores, it is a strong alternative to Qwen 3 8B. The NVIDIA Open Model License permits commercial use with some restrictions.

General PurposeReasoningCodeAgentic

Technical Specifications

Total Parameters9.0B

ArchitectureDense

Attention TypeGQA (Grouped Query Attention)

Hidden Dimensiond = 4,096

Transformer Layers40

Attention Heads32

KV Headsn_kv = 8

Head Dimensiond_head = 128

Activation FunctionSwiGLU

NormalizationRMSNorm

Position EmbeddingRoPE

System Requirements

Estimated VRAM at 10% overhead for different quantization methods and context sizes.

Quantization	1K ctx	128K ctx
Q4_K_M0.50 B/W ~97% of FP16	4.81Consumer GPU	24.65Datacenter GPU
Q8_01.00 B/W ~100% of FP16	9.46Consumer GPU	29.30Datacenter GPU
F162.00 B/W Reference	18.76Consumer GPU	38.61Datacenter GPU

Fits 24 GB consumer GPU

Fits 80 GB datacenter GPU

Requires cluster / multi-GPU

Other Nvidia Models

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Nemotron 3 Nano 30B-A3B (MoE)

Params

30.0B

Layers

Context

256K

3.0B active

Nemotron 3 Nano 4B

Params

4.0B

Layers

Context

256K

Llama-Nemotron 8B

Params

8.0B

Layers

Context

128K

Find the right GPU for Nemotron-Nano 9B v2

Use the interactive VRAM Calculator to see exactly how much memory you need at any quantization level, context length, and overhead setting.

Open VRAM Calculator Best GPU Guide VRAM Guide