Model Comparison

DeepSeek-V3.2-Exp vs Llama-3.3 Nemotron Super 49B v1

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2-Exp outperforms in 2 benchmarks (AIME 2025, GPQA), while Llama-3.3 Nemotron Super 49B v1 is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Mon Apr 20 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Mon Apr 20 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

635.1B diff

DeepSeek-V3.2-Exp has 635.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 1272.7% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
685.0B
DeepSeek-V3.2-Exp
49.9B
Llama-3.3 Nemotron Super 49B v1

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Mon Apr 20 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp 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-V3.2-Exp

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-V3.2-Exp was released on 2025-09-29, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

DeepSeek-V3.2-Exp is 7 months newer than Llama-3.3 Nemotron Super 49B v1.

DeepSeek-V3.2-Exp

Sep 29, 2025

6 months ago

6mo newer
Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.1 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-V3.2-Exp'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-V3.2-Exp's cutoff date.

DeepSeek-V3.2-Exp

—

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Higher AIME 2025 score (89.3% vs 58.4%)
Higher GPQA score (79.9% vs 66.7%)
NVIDIA

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
NVIDIA
Llama-3.3 Nemotron Super 49B v1

FAQ

Common questions about DeepSeek-V3.2-Exp vs Llama-3.3 Nemotron Super 49B v1

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is made by NVIDIA. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. 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%.
DeepSeek-V3.2-Exp supports 164K 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.
Key differences include licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.