Model Comparison

DeepSeek-V4-Flash-0731 vs Nemotron Nano 9B v2Which is better in 2026?

Comparing DeepSeek-V4-Flash-0731 and Nemotron Nano 9B v2 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V4-Flash-0731 vs Nemotron Nano 9B v2 — which is better?

DeepSeek-V4-Flash-0731 (by DeepSeek) and Nemotron Nano 9B v2 (by NVIDIA) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose DeepSeek-V4-Flash-0731 if…

  • you want the most recent training data — it shipped Jul 2026

Choose Nemotron Nano 9B v2 if…

  • you are already invested in the NVIDIA ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Flash-0731 and Nemotron Nano 9B v2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

295.1B diff

DeepSeek-V4-Flash-0731 has 295.1B more parameters than Nemotron Nano 9B v2, making it 3315.7% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
NVIDIA
Nemotron Nano 9B v2
8.9Bparameters
304.0B
DeepSeek-V4-Flash-0731
8.9B
Nemotron Nano 9B v2

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output65,536 tokens
NVIDIA
Nemotron Nano 9B v2
Input- tokens
Output- tokens
Mon Aug 03 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 is licensed under MIT, 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.

DeepSeek-V4-Flash-0731

MIT

Open weights

Nemotron Nano 9B v2

NVIDIA Open Model License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Nemotron Nano 9B v2 was released on 2025-08-18.

DeepSeek-V4-Flash-0731 is 12 months newer than Nemotron Nano 9B v2.

DeepSeek-V4-Flash-0731

Jul 31, 2026

3 days ago

11mo newer
Nemotron Nano 9B v2

Aug 18, 2025

11 months ago

Knowledge Cutoff

When training data ends

Nemotron Nano 9B v2 has a documented knowledge cutoff of 2024-09-01, while DeepSeek-V4-Flash-0731'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 DeepSeek-V4-Flash-0731's cutoff date.

DeepSeek-V4-Flash-0731

—

Nemotron Nano 9B v2

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (1,048,576 tokens)
NVIDIA

No standout differentiators in the data we have for this pair.

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-0731 and Nemotron Nano 9B v2 side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
Nemotron Nano 9B v2
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-0731
NVIDIA
Nemotron Nano 9B v2

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs Nemotron Nano 9B v2.

Which is better, DeepSeek-V4-Flash-0731 or Nemotron Nano 9B v2?

DeepSeek-V4-Flash-0731 (DeepSeek) and Nemotron Nano 9B v2 (NVIDIA) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V4-Flash-0731 compare to Nemotron Nano 9B v2 in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. 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 DeepSeek-V4-Flash-0731 and Nemotron Nano 9B v2?

DeepSeek-V4-Flash-0731 supports 1.0M 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 DeepSeek-V4-Flash-0731 and Nemotron Nano 9B v2?

Key differences include licensing (MIT vs NVIDIA Open Model License Agreement ). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and Nemotron Nano 9B v2?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and Nemotron Nano 9B v2 is developed by NVIDIA.

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