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Nvidia Nemotron Super 49B

Added Aug 8, 2025Open weights

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Llama-3.3-Nemotron-Super-49B-v1 is a model which offers a great tradeoff between model accuracy and efficiency. Efficiency (throughput) directly translates to savings. Using a novel Neural Architecture Search (NAS) approach, we greatly reduce the model's memory footprint, enabling larger workloads, as well as fitting the model on a single GPU at high workloads (H200). This NAS approach enables the selection of a desired point in the accuracy-efficiency tradeoff. For more information on the NAS approach, please refer to this paper.

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.15
Output
$0.15

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
16.4K

Side by side

Nvidia Nemotron Super 49B compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Nvidia Nemotron Super 49BnvidiaThis modelNemotron 3.5 Content SafetynvidiaRemove
Providernvidianvidia
Discovery tierOpen weightsOpen weights
AddedAug 8, 2025Sep 19, 2026
Limits
Context window128K131.07KBest
Max output16.38K32.77KBest
Average output—16 tokens
Pricing, USD per 1M tokens
Input$0.15$0.05Best
Output$0.15$0.15
Cache read—$0.025
Benchmark indexes
Intelligence Index7.3—
Math Index7.7—
Capabilities
ReasoningNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Nvidia Nemotron Super 49B
  • Nemotron 3.5 Content Safety

Intelligence Index

  • Nvidia Nemotron Super 49B7.3
  • Nemotron 3.5 Content Safety—

Nvidia Nemotron Super 49B: Better than 10% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Nvidia Nemotron Super 49B: 7.7
    • Nemotron 3.5 Content Safety: —

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Nvidia Nemotron Super 49B: 12.0%
    • Nemotron 3.5 Content Safety: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Nvidia Nemotron Super 49B: 3.8%
    • Nemotron 3.5 Content Safety: —

  • GPQA Diamond

    Graduate-level science questions

    • Nvidia Nemotron Super 49B: 51.7%
    • Nemotron 3.5 Content Safety: —

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Nvidia Nemotron Super 49B: 69.8%
    • Nemotron 3.5 Content Safety: —

  • IFBench

    Following precise output instructions

    • Nvidia Nemotron Super 49B: 39.5%
    • Nemotron 3.5 Content Safety: —

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Nvidia Nemotron Super 49B: 28.0%
    • Nemotron 3.5 Content Safety: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Nvidia Nemotron Super 49B: 7.7%
    • Nemotron 3.5 Content Safety: —

  • AIME

    Competition mathematics

    • Nvidia Nemotron Super 49B: 19.3%
    • Nemotron 3.5 Content Safety: —

  • MATH-500

    Competition math problems

    • Nvidia Nemotron Super 49B: 77.5%
    • Nemotron 3.5 Content Safety: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Nvidia Nemotron Super 49B: 0.0%
    • Nemotron 3.5 Content Safety: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Nvidia Nemotron Super 49B: 12.0%
    • Nemotron 3.5 Content Safety: —

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nvidia/Llama-3.3-Nemotron-Super-49B-v1",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="nvidia/Llama-3.3-Nemotron-Super-49B-v1",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

nvidia

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