FitMyLLM
NVIDIA/Dense

NVIDIANVIDIA-Nemotron-3-Nano-30B-A3B-BF16

Model Developer: NVIDIA Corporation

chatThinkingTool Use
31.6B
Parameters
256K
Context length
11
Benchmarks
14
Quantizations
1.0M
HF downloads
Architecture
Dense
Released
2025-12-04
Layers
52
KV Heads
2
Head Dim
128
Family
nemotron

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
13.9 GB
13.3 + 0.6 KV
low
IQ3_XS3.5
14.9 GB
14.3 + 0.6 KV
low
Q3_K_S3.64
15.5 GB
14.9 + 0.6 KV
low
IQ3_M3.76
15.9 GB
15.3 + 0.6 KV
low
Q3_K_M4
16.9 GB
16.3 + 0.6 KV
low
Q3_K_L4.3
18.1 GB
17.5 + 0.6 KV
moderate
IQ4_XS4.46
18.7 GB
18.1 + 0.6 KV
moderate
Q4_K_S4.67
19.5 GB
18.9 + 0.6 KV
moderate
Q4_K_M4.89
20.4 GB
19.8 + 0.6 KV
good
Q5_K_S5.57
23.1 GB
22.5 + 0.6 KV
good
Q5_K_M5.7
23.6 GB
23.0 + 0.6 KV
good
Q6_K6.56
27.0 GB
26.4 + 0.6 KV
excellent
Q8_08.5
34.7 GB
34.1 + 0.6 KV
lossless
FP1616
64.3 GB
63.7 + 0.6 KV
lossless

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

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READY TO RUN THIS?RENT BY THE HOUR

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Community Ratings

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Benchmarks (11)

IFEval83.2
BBH62.5
MATH55.4
MMLU-PRO47.8
GPQA Diamond39.9
LiveCodeBench36.0
MUSR22.3
GPQA18.9
AIME13.3
MATH-50013.3
HLE4.6

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run nemotron:31b

Tag may need adjustment — check ollama.com/library/nemotron 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 RTX A4500
20 GB VRAM • 640 GB/s
NVIDIA
$2000
Apple M4 Pro (24GB)
24 GB VRAM • 273 GB/s
APPLE
$1399
NVIDIA L4 24GB
24 GB VRAM • 300 GB/s
NVIDIA
$2500
Apple M2 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M3 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M4 (24GB)
24 GB VRAM • 120 GB/s
APPLE
$699
NVIDIA Tesla M40 24 GB
24 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla P10
24 GB VRAM • 694 GB/s
NVIDIA
NVIDIA Tesla P40
24 GB VRAM • 347 GB/s
NVIDIA
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000

Find the best GPU for NVIDIA-Nemotron-3-Nano-30B-A3B-BF16

Build Hardware for NVIDIA-Nemotron-3-Nano-30B-A3B-BF16

Model Developer: NVIDIA Corporation

▸ SPEC SHEET

NVIDIA-Nemotron-3-Nano-30B-A3B-BF1631.6B Dense.

▸ SPECIFICATIONS
PARAMETERS
31.6B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat
RELEASE DATE
2025-12-04
PROVIDER
NVIDIA
FAMILY
nemotron
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2513.3 GB82%
IQ3_XS3.514.3 GB84%
Q3_K_S3.6414.9 GB85%
IQ3_M3.7615.3 GB86%
Q3_K_M416.3 GB88%
Q3_K_L4.317.5 GB90%
IQ4_XS4.4618.1 GB92%
Q4_K_S4.6718.9 GB93%
Q4_K_M4.8919.8 GB94%
Q5_K_S5.5722.5 GB96%
Q5_K_M5.723.0 GB96%
Q6_K6.5626.4 GB97%
Q8_08.534.1 GB100%
FP161663.7 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO47.8
MATH55.4
IFEval83.2
BBH62.5
GPQA18.9
MUSR22.3
LiveCodeBench36.0
AIME13.3
MATH-50013.3
GPQA Diamond39.9
HLE4.6
§ 02RUN COMMAND

Run NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 locally with Ollama — needs 19.8 GB VRAM at Q4_K_M:

$ollama run nemotron:31b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M