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GPT-4o vs Nemotron Nano 9B v2

Nemotron Nano 9B v2 leads the LLM Stats Score 18.6 to 14.3.

OpenAI · NVIDIA · Updated for 2026

Which is better?

Nemotron Nano 9B v2 leads the overall LLM Stats Score 18.6 to 14.3, ranking #200 overall.

The models split the 2 individual benchmarks reported for both models evenly.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-4o

  • you want predictable pricing at $2.50/M input and $10.00/M output

Choose Nemotron Nano 9B v2

  • overall performance matters — it scores 18.6 and ranks #200 on LLM Stats
  • your work emphasizes coding — it leads those capability indexes
  • you want the most recent training data — it shipped Aug 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
14.3
#226
18.6
#200
16.0
#207
17.4
#198
-0.3
#235
14.6
#125
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$2.50 / M
— / M
Output price
$10.00 / M
— / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-4o
Nemotron Nano 9B v2
12.7#225
16.5#197
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

38 reported for GPT-4o · 6 for Nemotron Nano 9B v2

2 shared

GPT-4o outperforms in 1 benchmarks (GPQA), while Nemotron Nano 9B v2 is better at 1 benchmark (IFEval).

Both models are evenly matched across the benchmarks.

Fri Sep 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-4o specifies input context (128,000 tokens). Only GPT-4o specifies output context (16,384 tokens).

OpenAI
GPT-4o
Input128,000 tokens
Output16,384 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Fri Sep 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-4o supports multimodal inputs, whereas Nemotron Nano 9B v2 does not.

GPT-4o can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4o

Text
Images
Audio
Video

Nemotron Nano 9B v2

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4o is licensed under a proprietary license, while Nemotron Nano 9B v2 uses NVIDIA Open Model License Agreement .

License differences may affect how you can use these models in commercial or open-source projects.

GPT-4o

Proprietary

Closed source

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

GPT-4o was released on 2024-08-06, while Nemotron Nano 9B v2 was released on 2025-08-18.

Nemotron Nano 9B v2 is 13 months newer than GPT-4o.

GPT-4o

Aug 6, 2024

2.1 years ago

Nemotron Nano 9B v2

Aug 18, 2025

1.0 years ago

1.0yr newer

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while GPT-4o's cutoff date is not specified.

We can confirm Nemotron Nano 9B v2's training data extends to 2024-09-01, but cannot make a direct comparison without GPT-4o's cutoff date.

GPT-4o

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-4o and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

GPT-4o
✓ Preferred
Nemotron Nano 9B v2
Open in Playground

FAQ

Common questions about GPT-4o vs Nemotron Nano 9B v2.

Which is better, GPT-4o or Nemotron Nano 9B v2?

Nemotron Nano 9B v2 leads the LLM Stats Score 18.6 to 14.3. GPT-4o is made by OpenAI and Nemotron Nano 9B v2 is made by NVIDIA. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-4o compare to Nemotron Nano 9B v2 in benchmarks?

GPT-4o scores AI2D: 94.2%, DocVQA: 92.8%, ChartQA: 85.7%, MMLU: 85.7%, CharXiv-D: 85.3%. Nemotron Nano 9B v2 scores MATH-500: 97.8%, IFEval: 90.3%, AIME 2025: 72.1%, LiveCodeBench: 71.1%, BFCL_v3_MultiTurn: 66.9%.

What are the context window sizes for GPT-4o and Nemotron Nano 9B v2?

GPT-4o supports 128K tokens and Nemotron Nano 9B v2 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4o and Nemotron Nano 9B v2?

Key differences include LLM Stats Score (14.3 vs 18.6), multimodal support (yes vs no), licensing (Proprietary vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4o and Nemotron Nano 9B v2?

GPT-4o is developed by OpenAI and Nemotron Nano 9B v2 is developed by NVIDIA.