Model Comparison

DeepSeek-V2.5 vs Llama 3.1 Nemotron Ultra 253B v1

Comparing DeepSeek-V2.5 and Llama 3.1 Nemotron Ultra 253B v1 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V2.5 and Llama 3.1 Nemotron Ultra 253B v1 don'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

17.0B diff

Llama 3.1 Nemotron Ultra 253B v1 has 17.0B more parameters than DeepSeek-V2.5, making it 7.2% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
253.0Bparameters
236.0B
DeepSeek-V2.5
253.0B
Llama 3.1 Nemotron Ultra 253B v1

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1
Input- tokens
Output- tokens
Sun May 10 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Llama 3.1 Nemotron Ultra 253B v1 uses Llama 3.1 Community License.

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

DeepSeek-V2.5

deepseek

Open weights

Llama 3.1 Nemotron Ultra 253B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Llama 3.1 Nemotron Ultra 253B v1 was released on 2025-04-07.

Llama 3.1 Nemotron Ultra 253B v1 is 11 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

Llama 3.1 Nemotron Ultra 253B v1

Apr 7, 2025

1.1 years ago

11mo newer

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Ultra 253B v1 has a documented knowledge cutoff of 2023-12-01, while DeepSeek-V2.5's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron Ultra 253B v1's training data extends to 2023-12-01, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.

DeepSeek-V2.5

—

Llama 3.1 Nemotron Ultra 253B v1

Dec 2023

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (8,192 tokens)
NVIDIA

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
NVIDIA
Llama 3.1 Nemotron Ultra 253B v1

FAQ

Common questions about DeepSeek-V2.5 vs Llama 3.1 Nemotron Ultra 253B v1.

Which is better, DeepSeek-V2.5 or Llama 3.1 Nemotron Ultra 253B v1?

DeepSeek-V2.5 (DeepSeek) and Llama 3.1 Nemotron Ultra 253B 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-V2.5 compare to Llama 3.1 Nemotron Ultra 253B v1 in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Llama 3.1 Nemotron Ultra 253B v1 scores MATH-500: 97.0%, IFEval: 89.5%, GPQA: 76.0%, BFCL v2: 74.1%, AIME 2025: 72.5%.

What are the context window sizes for DeepSeek-V2.5 and Llama 3.1 Nemotron Ultra 253B v1?

DeepSeek-V2.5 supports 8K tokens and Llama 3.1 Nemotron Ultra 253B 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-V2.5 and Llama 3.1 Nemotron Ultra 253B v1?

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

Who makes DeepSeek-V2.5 and Llama 3.1 Nemotron Ultra 253B v1?

DeepSeek-V2.5 is developed by DeepSeek and Llama 3.1 Nemotron Ultra 253B v1 is developed by NVIDIA.