Model Comparison

DeepSeek-V4-Flash-0731 vs Llama-3.3 Nemotron Super 49B v1Which is better in 2026?

Comparing DeepSeek-V4-Flash-0731 and Llama-3.3 Nemotron Super 49B v1 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V4-Flash-0731 vs Llama-3.3 Nemotron Super 49B v1 — which is better?

DeepSeek-V4-Flash-0731 (by DeepSeek) and Llama-3.3 Nemotron Super 49B v1 (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 Llama-3.3 Nemotron Super 49B v1 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 Llama-3.3 Nemotron Super 49B v1don'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

254.1B diff

DeepSeek-V4-Flash-0731 has 254.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 509.2% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
304.0B
DeepSeek-V4-Flash-0731
49.9B
Llama-3.3 Nemotron Super 49B v1

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
Llama-3.3 Nemotron Super 49B v1
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 Llama-3.3 Nemotron Super 49B v1 uses Llama 3.1 Community License.

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

DeepSeek-V4-Flash-0731

MIT

Open weights

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

DeepSeek-V4-Flash-0731 is 17 months newer than Llama-3.3 Nemotron Super 49B v1.

DeepSeek-V4-Flash-0731

Jul 31, 2026

3 days ago

1.4yr newer
Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.4 years ago

Knowledge Cutoff

When training data ends

Llama-3.3 Nemotron Super 49B v1 has a documented knowledge cutoff of 2023-12-31, while DeepSeek-V4-Flash-0731's cutoff date is not specified.

We can confirm Llama-3.3 Nemotron Super 49B v1's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-V4-Flash-0731's cutoff date.

DeepSeek-V4-Flash-0731

—

Llama-3.3 Nemotron Super 49B v1

Dec 2023

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 Llama-3.3 Nemotron Super 49B v1 side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
Llama-3.3 Nemotron Super 49B v1
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-0731
NVIDIA
Llama-3.3 Nemotron Super 49B v1

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs Llama-3.3 Nemotron Super 49B v1.

Which is better, DeepSeek-V4-Flash-0731 or Llama-3.3 Nemotron Super 49B v1?

DeepSeek-V4-Flash-0731 (DeepSeek) and Llama-3.3 Nemotron Super 49B v1 (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 Llama-3.3 Nemotron Super 49B v1 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%. Llama-3.3 Nemotron Super 49B v1 scores MATH-500: 96.6%, MT-Bench: 91.7%, MBPP: 91.3%, Arena Hard: 88.3%, BFCL v2: 73.7%.

What are the context window sizes for DeepSeek-V4-Flash-0731 and Llama-3.3 Nemotron Super 49B v1?

DeepSeek-V4-Flash-0731 supports 1.0M tokens and Llama-3.3 Nemotron Super 49B v1 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 Llama-3.3 Nemotron Super 49B v1?

Key differences include licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and Llama-3.3 Nemotron Super 49B v1?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.

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