Model Comparison

DeepSeek-V2.5 vs Llama 3.1 Nemotron Nano 8B V1Which is better in 2026?

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Verdict: DeepSeek-V2.5 vs Llama 3.1 Nemotron Nano 8B V1 — which is better?

DeepSeek-V2.5 (by DeepSeek) and Llama 3.1 Nemotron Nano 8B 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.

DeepSeek-V2.5 outperforms in 1 benchmarks (MT-Bench), while Llama 3.1 Nemotron Nano 8B V1 is better at 0 benchmarks. DeepSeek-V2.5 significantly outperforms across most benchmarks.

Choose DeepSeek-V2.5 if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks

Choose Llama 3.1 Nemotron Nano 8B V1 if…

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

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V2.5 outperforms in 1 benchmarks (MT-Bench), while Llama 3.1 Nemotron Nano 8B V1 is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Mon Jul 27 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

228.0B diff

DeepSeek-V2.5 has 228.0B more parameters than Llama 3.1 Nemotron Nano 8B V1, making it 2850.0% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
NVIDIA
Llama 3.1 Nemotron Nano 8B V1
8.0Bparameters
236.0B
DeepSeek-V2.5
8.0B
Llama 3.1 Nemotron Nano 8B 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 Nano 8B V1
Input- tokens
Output- tokens
Mon Jul 27 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Llama 3.1 Nemotron Nano 8B 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 Nano 8B 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 Nano 8B V1 was released on 2025-03-18.

Llama 3.1 Nemotron Nano 8B V1 is 10 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.2 years ago

Llama 3.1 Nemotron Nano 8B V1

Mar 18, 2025

1.4 years ago

10mo newer

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Nano 8B V1 has a documented knowledge cutoff of 2023-12-31, while DeepSeek-V2.5's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron Nano 8B V1's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.

DeepSeek-V2.5

—

Llama 3.1 Nemotron Nano 8B V1

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (8,192 tokens)
Higher MT-Bench score (90.2% vs 81.0%)
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-V2.5 and Llama 3.1 Nemotron Nano 8B V1 side-by-side, then vote on the output you prefer.

DeepSeek-V2.5
✓ Preferred
Llama 3.1 Nemotron Nano 8B V1
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
NVIDIA
Llama 3.1 Nemotron Nano 8B V1

FAQ

Common questions about DeepSeek-V2.5 vs Llama 3.1 Nemotron Nano 8B V1.

Which is better, DeepSeek-V2.5 or Llama 3.1 Nemotron Nano 8B V1?

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is made by DeepSeek and Llama 3.1 Nemotron Nano 8B V1 is made by NVIDIA. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V2.5 compare to Llama 3.1 Nemotron Nano 8B 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 Nano 8B V1 scores MATH-500: 95.4%, MBPP: 84.6%, MT-Bench: 81.0%, IFEval: 79.3%, BFCL v2: 63.6%.

What are the context window sizes for DeepSeek-V2.5 and Llama 3.1 Nemotron Nano 8B V1?

DeepSeek-V2.5 supports 8K tokens and Llama 3.1 Nemotron Nano 8B 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 Nano 8B 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 Nano 8B V1?

DeepSeek-V2.5 is developed by DeepSeek and Llama 3.1 Nemotron Nano 8B V1 is developed by NVIDIA.

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