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OpenReasoning Nemotron 32B

Added Aug 21, 2025Open weights

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OpenReasoning-Nemotron-32B is a reasoning model derived from Qwen2.5-32B-Instruct, post-trained for math, science, and code solution generation. Evaluated with up to 64K output tokens. Available in multiple sizes: 1.5B, 7B, 14B, and 32B.

  • Reasoning
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.10
Output
$0.40

Reference prices as published by the model provider. API example

Specifications

Context window
32.8K
Max output
—

Side by side

OpenReasoning Nemotron 32B compared

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

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OpenReasoning Nemotron 32BnvidiaThis modelNvidia Nemotron 3.5 Super VLnvidiaRemove
Providernvidianvidia
Discovery tierOpen weightsOpen weights
AddedAug 21, 2025Oct 15, 2026
Limits
Context window32.77K262.14KBest
Max output—16.38K
Average output—1.1K tokens
Pricing, USD per 1M tokens
Input$0.10Best$0.15
Output$0.40Best$0.50
Cache read—$0.02
Performance
Throughput—621.5 tok/s
Time to first token—1.7 s
Request success (24h)—98.3%
Benchmark indexes
Intelligence Index—26.5
Capabilities
ReasoningYesYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
Video inputNoYes
Reasoning effort—none, medium, high

Public evaluations

Benchmarks

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

  • OpenReasoning Nemotron 32B
  • Nvidia Nemotron 3.5 Super VL

Intelligence Index

  • OpenReasoning Nemotron 32B—
  • Nvidia Nemotron 3.5 Super VL26.5
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 14.8%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 2.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 999 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 1,162 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 8.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 69.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 13.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 30.7%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 0.0%

  • SciCode

    Scientific computing in Python

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 47.8%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • OpenReasoning Nemotron 32B: —
    • Nvidia Nemotron 3.5 Super VL: 69.0%

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": "pamanseau/OpenReasoning-Nemotron-32B",
    "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="pamanseau/OpenReasoning-Nemotron-32B",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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