NVIDIA Nemotron 3 Super
nvidiaothertext

NVIDIA Nemotron 3 Super

Updated Jun 7, 2026
Parameters
67.2B
Context
262,144
License
other
Updated
Jun 7, 2026

Intelligence benchmarks

Artificial Analysis indexes - compared with the best open and proprietary models

Intelligence

36.0

AA Index

Coding

31.2

AA Index

Agentic

40.2

AA Index

Intelligence Index - NVIDIA Nemotron 3 Super vs. the field

Best open-weight models (you can run locally) and leading proprietary models for context.

Claude Opus 4.8 (max)
61.4
closed
GPT-5.5 (xhigh)
60.2
closed
Claude Opus 4.7 (max)
57.3
closed
Gemini 3.1 Pro Preview
57.2
closed
Qwen3.7 Max
56.6
closed
Kimi K2.6
53.9
open
MiMo-V2.5-Pro
53.8
open
NVIDIA Nemotron 3 Super
36
open

Coding Index comparison

GPT-5.5 (xhigh)
59.1
closed
Claude Opus 4.8 (max)
56.7
closed
Gemini 3.1 Pro Preview
55.5
closed
Claude Opus 4.7 (Non-reasoning, high)
53.1
closed
GPT-5.3 Codex (xhigh)
53.1
closed
DeepSeek V4 Pro (Max)
47.5
open
Kimi K2.6
47.1
open
NVIDIA Nemotron 3 Super
31.2
open

Agentic Index comparison

Claude Opus 4.8 (max)
77.8
closed
GPT-5.5 (xhigh)
74.1
closed
Claude Opus 4.7 (max)
71.3
closed
Gemini 3.5 Flash (medium)
70.4
closed
MiniMax-M3
68.6
closed
MiMo-V2.5-Pro
67.4
open
DeepSeek V4 Pro (Max)
67.2
open
NVIDIA Nemotron 3 Super
40.2
open

Benchmark data from Artificial Analysis · updated 2026-06-07.

Standard benchmarks

Performance across standard evaluations

BenchmarkScore
GPQA80

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Too big for 24 GB at any quant
0 of 4 quantizations fit NVIDIA Nemotron 3 Super with real runtime overhead.

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

NVIDIA Nemotron 3 Super is a 67.2B-parameter other model from NVIDIA. It scores 36 on the Artificial Analysis Intelligence Index (coding 31.2). At Q4_K_M it needs roughly 39 GB of VRAM, placing it in the 24–48 GB hardware tier.

Benchmarks

Artificial Analysis Intelligence Index - NVIDIA Nemotron 3 Super vs. leading closed models:

ModelIntelligenceCodingGPQA
NVIDIA Nemotron 3 Super3631.280
GPT-5.5 (xhigh)60.259.193.5
Claude Opus 4.8 (max)61.456.792
Gemini 3.1 Pro Preview57.255.594.1
Grok 4.3 (high)53.24190.1

Source: Artificial Analysis (2026-06-07).

Popularity

NVIDIA Nemotron 3 Super has 1,569,632 downloads in the last month on HuggingFace and 342 likes.

Frequently asked

Quick answers to common questions

How much VRAM does NVIDIA Nemotron 3 Super need?

NVIDIA Nemotron 3 Super with 67.2B parameters needs approximately 39 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is NVIDIA Nemotron 3 Super better than other nvidia models?

NVIDIA Nemotron 3 Super has 67.2B parameters with 262,144 context - a strong choice for general use.

What license is NVIDIA Nemotron 3 Super under?

NVIDIA Nemotron 3 Super is released under the other license, making it suitable for most commercial and personal projects.

What hardware runs NVIDIA Nemotron 3 Super well?

With 67.2B parameters, NVIDIA Nemotron 3 Super requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for NVIDIA Nemotron 3 Super?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~48 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can NVIDIA Nemotron 3 Super's context window handle?

NVIDIA Nemotron 3 Super supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.

What models compete with NVIDIA Nemotron 3 Super?

NVIDIA Nemotron 3 Super competes with other 34B–101B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec

Comments coming soon

Configure NEXT_PUBLIC_GISCUS_REPO_ID and NEXT_PUBLIC_GISCUS_CATEGORY_ID at giscus.app to enable.