FitMyLLM
NVIDIA/Dense

NVIDIANemotron 3 Nano 4B

Nemotron 3 Nano — compact model with tool use and function calling.

chatcodingreasoningmathtool_useThinkingTool Use
3.97B
Parameters
256K
Context length
15
Benchmarks
6
Quantizations
100K
HF downloads
Architecture
Dense
Released
2026-03-16
Layers
42
KV Heads
8
Head Dim
128
Family
nemotron

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
4.9 GB
2.9 + 2.0 KV
good
Q5_K_S5.57
5.2 GB
3.3 + 2.0 KV
good
Q5_K_M5.7
5.3 GB
3.3 + 2.0 KV
good
Q6_K6.56
5.7 GB
3.7 + 2.0 KV
excellent
Q8_08.5
6.7 GB
4.7 + 2.0 KV
lossless
FP1616
10.4 GB
8.4 + 2.0 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
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Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (15)

MATH95.4
IFEval88.0
IFBench58.2
GPQA53.2
GPQA Diamond51.3
τ²-Bench28.1
MMLU-PRO18.1
AA Long Context16.7
SciCode16.4
AA Intelligence14.7
BBH14.2
AA Coding10.0
Terminal-Bench6.8
HLE4.8
MUSR4.6

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run nemotron-3-nano:4b

Tag may need adjustment — check ollama.com/library/nemotron-3-nano for available tags.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA Tesla C2050
3 GB VRAM • 144 GB/s
NVIDIA
NVIDIA Tesla M2050
3 GB VRAM • 148 GB/s
NVIDIA
NVIDIA Tesla S2050
3 GB VRAM • 148 GB/s
NVIDIA

Find the best GPU for Nemotron 3 Nano 4B

Build Hardware for Nemotron 3 Nano 4B

Nemotron 3 Nano — compact model with tool use and function calling.

▸ SPEC SHEET

Nemotron 3 Nano 4B3.97B Dense.

▸ SPECIFICATIONS
PARAMETERS
3.97B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, reasoning, math, tool_use
RELEASE DATE
2026-03-16
PROVIDER
NVIDIA
FAMILY
nemotron
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.892.9 GB94%
Q5_K_S5.573.3 GB96%
Q5_K_M5.73.3 GB96%
Q6_K6.563.7 GB97%
Q8_08.54.7 GB100%
FP16168.4 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO18.1
MATH95.4
IFEval88.0
BBH14.2
GPQA53.2
MUSR4.6
aa_ifbench58.2
aa_terminal_bench6.8
aa_tau228.1
aa_scicode16.4
aa_lcr16.7
GPQA Diamond51.3
HLE4.8
AA Intelligence14.7
AA Coding10.0
§ 02RUN COMMAND

Run Nemotron 3 Nano 4B locally with Ollama — needs 2.9 GB VRAM at Q4_K_M:

$ollama run nemotron-3-nano:4b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M