The AI arena is free today

Open Superagent

DeepSeek-R1 vs Llama-3.3 Nemotron Super 49B v1

Comparing DeepSeek-R1 and Llama-3.3 Nemotron Super 49B v1 across benchmarks, pricing, and capabilities.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

DeepSeek-R1 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-R1

  • you want predictable pricing at $0.55/M input and $2.19/M output

Choose Llama-3.3 Nemotron Super 49B v1

  • you want the most recent training data — it shipped Mar 2025

At a glance

The differences that matter most.

DeepSeek-R1
DeepSeek
Llama-3.3 Nemotron Super 49B v1
NVIDIA
Benchmark wins
—
—
Input price
$0.55 / M
— / M
Output price
$2.19 / M
— / M
Context window
131,072
—

Individual benchmarks

0 reported for DeepSeek-R1 · 7 for Llama-3.3 Nemotron Super 49B v1

No common benchmarks found

DeepSeek-R1 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.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

621.1B diff

DeepSeek-R1 has 621.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 1244.7% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
671.0B
DeepSeek-R1
49.9B
Llama-3.3 Nemotron Super 49B v1

Context Window

Maximum input and output token capacity

Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 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-R1

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-R1 was released on 2025-01-20, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

Llama-3.3 Nemotron Super 49B v1 is 2 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.6 years ago

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.5 years ago

1mo newer

Knowledge Cutoff

When training data ends

Llama-3.3 Nemotron Super 49B v1 has a documented knowledge cutoff of 2023-12-31, while DeepSeek-R1'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-R1's cutoff date.

DeepSeek-R1

—

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-R1 and Llama-3.3 Nemotron Super 49B v1 side-by-side, then vote on the output you prefer.

DeepSeek-R1
✓ Preferred
Llama-3.3 Nemotron Super 49B v1
Open in Playground

FAQ

Common questions about DeepSeek-R1 vs Llama-3.3 Nemotron Super 49B v1.

Which is better, DeepSeek-R1 or Llama-3.3 Nemotron Super 49B v1?

DeepSeek-R1 (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-R1 compare to Llama-3.3 Nemotron Super 49B v1 in benchmarks?

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-R1 and Llama-3.3 Nemotron Super 49B v1?

DeepSeek-R1 supports 131K 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-R1 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-R1 and Llama-3.3 Nemotron Super 49B v1?

DeepSeek-R1 is developed by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.

Related comparisons