Model Comparison
DeepSeek-V4-Flash-0731 vs Nemotron 3 Nano (30B A3B)Which is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and Nemotron 3 Nano (30B A3B) across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs Nemotron 3 Nano (30B A3B) — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and Nemotron 3 Nano (30B A3B) (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.
On price, Nemotron 3 Nano (30B A3B) is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V4-Flash-0731 if…
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Nemotron 3 Nano (30B A3B) if…
- cost matters — it's about 1.1x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and Nemotron 3 Nano (30B A3B)don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 1.5x more expensive than Nemotron 3 Nano (30B A3B) ($0.06/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 1.3x cheaper than Nemotron 3 Nano (30B A3B) ($0.24/1M tokens).
In conclusion, DeepSeek-V4-Flash-0731 is more expensive than Nemotron 3 Nano (30B A3B).*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 272.0B more parameters than Nemotron 3 Nano (30B A3B), making it 850.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Nemotron 3 Nano (30B A3B)'s 262,144 tokens. Nemotron 3 Nano (30B A3B) can generate longer responses up to 262,144 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Nemotron 3 Nano (30B A3B) uses NVIDIA Open Model License Agreement .
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
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 3 Nano (30B A3B) was released on 2025-12-15.
DeepSeek-V4-Flash-0731 is 8 months newer than Nemotron 3 Nano (30B A3B).
Jul 31, 2026
5 days ago
7mo newerDec 15, 2025
7 months ago
Knowledge Cutoff
When training data ends
Nemotron 3 Nano (30B A3B) has a documented knowledge cutoff of 2025-11-28, while DeepSeek-V4-Flash-0731's cutoff date is not specified.
We can confirm Nemotron 3 Nano (30B A3B)'s training data extends to 2025-11-28, but cannot make a direct comparison without DeepSeek-V4-Flash-0731's cutoff date.
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Nov 2025
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Fireworks, Novita. Nemotron 3 Nano (30B A3B) is available from DeepInfra.
DeepSeek-V4-Flash-0731
Nemotron 3 Nano (30B A3B)
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Nemotron 3 Nano (30B A3B) side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Nemotron 3 Nano (30B A3B).