FitMyLLM
NVIDIA/Mixture of Experts

NVIDIANemotron 3 Super 120B

NVIDIA's hybrid Mamba-Transformer MoE. 120B total, 12B active. 1M context. 2.2x faster than gpt-oss-120B.

chatcodingreasoningtool_useagentic
120B
Parameters (12B active)
1024K
Context length
13
Benchmarks
17
Quantizations
Architecture
MoE
Released
2026-03-11
Layers
80
KV Heads
8
Head Dim
128
Family
nemotron

Quantization Options

QuantBitsVRAMQuality
IQ2_XXS2.3836.2 GBlow
IQ2_M2.9344.4 GBlow
Q2_K3.1647.9 GBlow
IQ3_XXS3.2549.2 GBlow
IQ3_XS3.553.0 GBlow
Q3_K_S3.6455.1 GBlow
IQ3_M3.7656.9 GBlow
Q3_K_M460.5 GBlow
Q3_K_L4.365.0 GBmoderate
IQ4_XS4.4667.4 GBmoderate
Q4_K_S4.6770.5 GBmoderate
Q4_K_M4.8973.8 GBgood
Q5_K_S5.5784.0 GBgood
Q5_K_M5.786.0 GBgood
Q6_K6.5698.9 GBexcellent
Q8_08.5128.0 GBlossless
FP1616240.5 GBlossless

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

▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN NEMOTRON 3 SUPER 120B NOW

Rent on RunPod →Or Vast.ai →

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (13)

AIME90.2
MMLU-PRO83.7
LiveCodeBench81.2
GPQA Diamond79.2
IFBench71.5
τ²-Bench67.8
SWE-bench60.5
AA Long Context60.0
AA Intelligence36.0
SciCode36.0
AA Coding31.2
Terminal-Bench28.8
HLE19.2

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run nemotron:120b-q4_K_M

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
HuggingFaceGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA H100 SXM5 80GB
80 GB VRAM • 3350 GB/s
NVIDIA
$25000
NVIDIA H100 PCIe 80GB
80 GB VRAM • 2000 GB/s
NVIDIA
$25000
NVIDIA A100 SXM 80GB
80 GB VRAM • 2039 GB/s
NVIDIA
$10000
NVIDIA A100 PCIe 80GB
80 GB VRAM • 1935 GB/s
NVIDIA
$10000
NVIDIA A100 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$15000
NVIDIA A100 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
$10000
NVIDIA A100X
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 80 GB
80 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 CNX
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA A800 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A800 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 SXM5
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA RTX 6000D
84 GB VRAM • 1570 GB/s
NVIDIA
$7500
NVIDIA B200
90 GB VRAM • 4100 GB/s
NVIDIA
$30000
NVIDIA H100 NVL 94 GB
94 GB VRAM • 3940 GB/s
NVIDIA
$30000
NVIDIA H100 SXM5 94 GB
94 GB VRAM • 3360 GB/s
NVIDIA
$25000
RTX Pro 6000
96 GB VRAM • 1792 GB/s
NVIDIA
$8565
NVIDIA H100 PCIe 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
Intel Data Center GPU Max 1350
96 GB VRAM • 2460 GB/s
INTEL
NVIDIA RTX PRO 6000 Blackwell Server
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
NVIDIA RTX PRO 6000 Blackwell
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
AMD Instinct MI300A
120 GB VRAM • 5300 GB/s
AMD
$12000
Apple M4 Max (128GB)
128 GB VRAM • 546 GB/s
APPLE
$3999
AMD Instinct MI250X
128 GB VRAM • 3277 GB/s
AMD
$10000
Apple M1 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$4999
Apple M2 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$3999
AMD Radeon Instinct MI250
128 GB VRAM • 3280 GB/s
AMD
$12000

Find the best GPU for Nemotron 3 Super 120B

Build Hardware for Nemotron 3 Super 120B
▸ SPEC SHEET

Nemotron 3 Super 120B — 120B MoE.

▸ SPECIFICATIONS
PARAMETERS
120B (12B active)
ARCHITECTURE
Mixture of Experts
CONTEXT LENGTH
1024K tokens
CAPABILITIES
chat, coding, reasoning, tool_use, agentic
RELEASE DATE
2026-03-11
PROVIDER
NVIDIA
FAMILY
nemotron
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ2_XXS2.3836.2 GB65%
IQ2_M2.9344.4 GB75%
Q2_K3.1647.9 GB78%
IQ3_XXS3.2549.2 GB82%
IQ3_XS3.553.0 GB84%
Q3_K_S3.6455.1 GB85%
IQ3_M3.7656.9 GB86%
Q3_K_M460.5 GB88%
Q3_K_L4.365.0 GB90%
IQ4_XS4.4667.4 GB92%
Q4_K_S4.6770.5 GB93%
Q4_K_M4.8973.8 GB94%
Q5_K_S5.5784.0 GB96%
Q5_K_M5.786.0 GB96%
Q6_K6.5698.9 GB97%
Q8_08.5128.0 GB100%
FP1616240.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO83.7
LiveCodeBench81.2
SWE-bench60.5
AIME90.2
GPQA Diamond79.2
HLE19.2
AA Intelligence36.0
AA Coding31.2
aa_ifbench71.5
aa_terminal_bench28.8
aa_tau267.8
aa_scicode36.0
aa_lcr60.0
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA H100 SXM5 80GB
80 GB · 3350 GB/s
NVIDIA H100 PCIe 80GB
80 GB · 2000 GB/s
NVIDIA A100 SXM 80GB
80 GB · 2039 GB/s
NVIDIA A100 PCIe 80GB
80 GB · 1935 GB/s
NVIDIA A100 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA A100 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A100X
80 GB · 2040 GB/s
NVIDIA H100 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H100 SXM5 80 GB
80 GB · 3360 GB/s
NVIDIA H100 CNX
80 GB · 2040 GB/s
NVIDIA A800 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A800 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA H800 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H800 SXM5
80 GB · 3360 GB/s
NVIDIA RTX 6000D
84 GB · 1570 GB/s