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Nemotron 4 340BvsGPT-o3

NVIDIA vs OpenAI — Side-by-side model comparison

GPT-o3 leads 4/5 categories

Head-to-Head Comparison

MetricNemotron 4 340BGPT-o3
Provider
Arena Rank
#2
Context Window
4K
200K
Input Pricing
Free (open)/1M tokens
$2.00/1M tokens
Output Pricing
Free (open)/1M tokens
$8.00/1M tokens
Parameters
340B
Undisclosed
Open Source
Yes
No
Best For
Synthetic data generation, training pipelines
Advanced reasoning, agentic tasks, research
Release Date
Jun 14, 2024
Apr 16, 2025

Nemotron 4 340B

Nemotron 4 340B is NVIDIA's large language model designed specifically for generating high-quality synthetic training data. With 340 billion parameters, it can produce diverse, accurate training examples for fine-tuning smaller models. NVIDIA released it to accelerate the development of custom AI models, recognizing that high-quality training data is often the biggest bottleneck in model development.

View NVIDIA profile →

GPT-o3

GPT-o3 is OpenAI's most advanced reasoning model, succeeding o1 as the frontier of deliberative AI. It uses an enhanced chain-of-thought approach where the model spends more compute time 'thinking' before responding, dramatically improving performance on complex STEM, mathematical, and logical reasoning tasks. With a 200K token context window and the ability to use tools during reasoning, o3 represents a significant leap in AI problem-solving capabilities. It achieved state-of-the-art results on the ARC-AGI benchmark, demonstrating near-human performance on novel reasoning challenges. The model is particularly strong at multi-step mathematical proofs, complex code debugging, and scientific analysis where careful step-by-step reasoning is essential. Originally priced at a premium, an 80% price reduction in June 2025 made o3 accessible to a much broader range of developers and applications.

View OpenAI profile →

Key Differences: Nemotron 4 340B vs GPT-o3

1

GPT-o3 supports a larger context window (200K), allowing it to process longer documents in a single request.

2

Nemotron 4 340B is open-source (free to self-host and fine-tune) while GPT-o3 is proprietary (API-only access).

N

When to use Nemotron 4 340B

  • +You need to self-host or fine-tune the model
  • +Your use case involves synthetic data generation, training pipelines
View full Nemotron 4 340B specs →
G

When to use GPT-o3

  • +You need to process long documents (200K context)
  • +You prefer a managed API without infrastructure overhead
  • +Your use case involves advanced reasoning, agentic tasks, research
View full GPT-o3 specs →

The Verdict

GPT-o3 wins our head-to-head comparison with 4 out of 5 category wins. It's the stronger choice for advanced reasoning, agentic tasks, research, though Nemotron 4 340B holds an edge in synthetic data generation, training pipelines.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Nemotron 4 340B or GPT-o3?
In our head-to-head comparison, GPT-o3 leads in 4 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). GPT-o3 excels at advanced reasoning, agentic tasks, research, while Nemotron 4 340B is better suited for synthetic data generation, training pipelines. The best choice depends on your specific requirements, budget, and use case.
How does Nemotron 4 340B pricing compare to GPT-o3?
Nemotron 4 340B charges Free (open) per 1M input tokens and Free (open) per 1M output tokens. GPT-o3 charges $2.00 per 1M input tokens and $8.00 per 1M output tokens. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Nemotron 4 340B and GPT-o3?
Nemotron 4 340B supports a 4K token context window, while GPT-o3 supports 200K tokens. GPT-o3 can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Nemotron 4 340B or GPT-o3 for free?
Nemotron 4 340B is a paid API model starting at Free (open) per 1M input tokens. GPT-o3 is a paid API model starting at $2.00 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Nemotron 4 340B or GPT-o3?
Nemotron 4 340B's arena rank is not yet available, while GPT-o3 holds rank #2. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Nemotron 4 340B or GPT-o3 better for coding?
Nemotron 4 340B's primary strength is synthetic data generation, training pipelines. GPT-o3's primary strength is advanced reasoning, agentic tasks, research. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.