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DeepSeek-R1-0528 vs Llama 3.1 Nemotron Nano 8B V1

DeepSeek-R1-0528 leads the LLM Stats Score 24.1 to 4.8.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

DeepSeek-R1-0528 leads the overall LLM Stats Score 24.1 to 4.8, ranking #173 overall.

In the 2 individual benchmarks reported for both models, DeepSeek-R1-0528 wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-R1-0528

  • overall performance matters — it scores 24.1 and ranks #173 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped May 2025

Choose Llama 3.1 Nemotron Nano 8B V1

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

DeepSeek-R1-0528
DeepSeek
Llama 3.1 Nemotron Nano 8B V1
NVIDIA
Core performance indexes
LLM Stats Score
24.1
#173
4.8
#306
Reasoning
23.7
#169
5.3
#301
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.50 / M
— / M
Output price
$2.15 / M
— / M
Context window
163,840
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-R1-0528
Llama 3.1 Nemotron Nano 8B V1
Math
26.2#105
8.8#258
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for DeepSeek-R1-0528 · 7 for Llama 3.1 Nemotron Nano 8B V1

2 shared

DeepSeek-R1-0528 outperforms in 2 benchmarks (AIME 2025, GPQA), while Llama 3.1 Nemotron Nano 8B V1 is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Wed Sep 23 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

663.0B diff

DeepSeek-R1-0528 has 663.0B more parameters than Llama 3.1 Nemotron Nano 8B V1, making it 8287.5% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
NVIDIA
Llama 3.1 Nemotron Nano 8B V1
8.0Bparameters
671.0B
DeepSeek-R1-0528
8.0B
Llama 3.1 Nemotron Nano 8B V1

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (163,840 tokens). Only DeepSeek-R1-0528 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-R1-0528
Input163,840 tokens
Output163,840 tokens
NVIDIA
Llama 3.1 Nemotron Nano 8B V1
Input- tokens
Output- tokens
Wed Sep 23 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, 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-R1-0528

MIT

Open weights

Llama 3.1 Nemotron Nano 8B V1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Llama 3.1 Nemotron Nano 8B V1 was released on 2025-03-18.

DeepSeek-R1-0528 is 2 months newer than Llama 3.1 Nemotron Nano 8B V1.

DeepSeek-R1-0528

May 28, 2025

1.3 years ago

2mo newer
Llama 3.1 Nemotron Nano 8B V1

Mar 18, 2025

1.5 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron Nano 8B V1 has a documented knowledge cutoff of 2023-12-31, while DeepSeek-R1-0528'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-R1-0528's cutoff date.

DeepSeek-R1-0528

—

Llama 3.1 Nemotron Nano 8B V1

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-R1-0528 and Llama 3.1 Nemotron Nano 8B V1 side-by-side, then vote on the output you prefer.

DeepSeek-R1-0528
✓ Preferred
Llama 3.1 Nemotron Nano 8B V1
Open in Playground

FAQ

Common questions about DeepSeek-R1-0528 vs Llama 3.1 Nemotron Nano 8B V1.

Which is better, DeepSeek-R1-0528 or Llama 3.1 Nemotron Nano 8B V1?

DeepSeek-R1-0528 leads the LLM Stats Score 24.1 to 4.8. DeepSeek-R1-0528 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 capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-R1-0528 compare to Llama 3.1 Nemotron Nano 8B V1 in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. 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-R1-0528 and Llama 3.1 Nemotron Nano 8B V1?

DeepSeek-R1-0528 supports 164K 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-R1-0528 and Llama 3.1 Nemotron Nano 8B V1?

Key differences include LLM Stats Score (24.1 vs 4.8), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1-0528 and Llama 3.1 Nemotron Nano 8B V1?

DeepSeek-R1-0528 is developed by DeepSeek and Llama 3.1 Nemotron Nano 8B V1 is developed by NVIDIA.

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