How much VRAM does Nemotron 3 Nano 4B need?

Nemotron 3 Nano 4B 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 3 Nano 4B on a consumer GPU?

Yes, Nemotron 3 Nano 4B 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 12 GB or larger GPU with at least 8 GB VRAM for reasonable context lengths.

What is Nemotron 3 Nano 4B's context window?

Nemotron 3 Nano 4B supports a maximum context window of 262,144 tokens. The default context is 16,384 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 3 Nano 4B?

For Nemotron 3 Nano 4B, 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 3 Nano 4B compare to similar models?

Nemotron 3 Nano 4B is a 4.0B 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 3 Nano 4B

Nemotron 3 Nano 4B is a dense transformer language model from the Nvidia family, containing 4B parameters across 32 layers. It supports up to 262K tokens of context with a hidden dimension of 2560 and 8 KV heads for efficient grouped-query …

4.0B

Parameters

256K

Max Context

Dense

Architecture

—

Released

Text

Modality

About Nemotron 3 Nano 4B

On-Device

Technical Specifications

Total Parameters4.0B

ArchitectureDense

Attention TypeGQA (Grouped Query Attention)

Hidden Dimensiond = 2,560

Transformer Layers32

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	195K ctx	256K ctx
Q4_K_M0.50 B/W ~97% of FP16	2.19Consumer GPU	26.48Datacenter GPU	34.07Datacenter GPU
Q8_01.00 B/W ~100% of FP16	4.26Consumer GPU	28.55Datacenter GPU	36.14Datacenter GPU
F162.00 B/W Reference	8.40Consumer GPU	32.68Datacenter GPU	40.27Datacenter GPU

Fits 24 GB consumer GPU

Fits 80 GB datacenter GPU

Requires cluster / multi-GPU

Other Nvidia Models

View All

Nemotron-Nano 9B v2

Params

9.0B

Layers

Context

128K

Nemotron 3 Nano 30B-A3B (MoE)

Params

30.0B

Layers

Context

256K

3.0B active

Llama-Nemotron 8B

Params

8.0B

Layers

Context

128K

Find the right GPU for Nemotron 3 Nano 4B

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