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DeepSeek-V4-Pro-0813 vs Llama-3.3 Nemotron Super 49B v1

Comparing DeepSeek-V4-Pro-0813 and Llama-3.3 Nemotron Super 49B v1 across benchmarks, pricing, and capabilities.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 and Llama-3.3 Nemotron Super 49B v1 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Pro-0813

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

Choose Llama-3.3 Nemotron Super 49B v1

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

DeepSeek-V4-Pro-0813
DeepSeek
Llama-3.3 Nemotron Super 49B v1
NVIDIA
Benchmark wins
—
—
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576
—
Released
Aug 2026
Mar 2025
License
MIT
Llama 3.1 Community License

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V4-Pro-0813 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

Playground indexes and blind preference scores

Model Size

Parameter count comparison

1550.1B diff

DeepSeek-V4-Pro-0813 has 1550.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 3106.4% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
1600.0B
DeepSeek-V4-Pro-0813
49.9B
Llama-3.3 Nemotron Super 49B v1

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Tue Aug 25 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Pro-0813 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-Pro-0813

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-Pro-0813 was released on 2026-08-13, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

DeepSeek-V4-Pro-0813 is 17 months newer than Llama-3.3 Nemotron Super 49B v1.

DeepSeek-V4-Pro-0813

Aug 13, 2026

1 weeks 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-Pro-0813'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-Pro-0813's cutoff date.

DeepSeek-V4-Pro-0813

—

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and Llama-3.3 Nemotron Super 49B v1 side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
Llama-3.3 Nemotron Super 49B v1
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs Llama-3.3 Nemotron Super 49B v1.

Which is better, DeepSeek-V4-Pro-0813 or Llama-3.3 Nemotron Super 49B v1?

DeepSeek-V4-Pro-0813 (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-Pro-0813 compare to Llama-3.3 Nemotron Super 49B v1 in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. 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-Pro-0813 and Llama-3.3 Nemotron Super 49B v1?

DeepSeek-V4-Pro-0813 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-Pro-0813 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-Pro-0813 and Llama-3.3 Nemotron Super 49B v1?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.

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