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DeepSeek-V3 vs Llama 3.1 Nemotron 70B Instruct

DeepSeek-V3 leads the LLM Stats Score 15.7 to 0.4.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

DeepSeek-V3 leads the overall LLM Stats Score 15.7 to 0.4, ranking #231 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V3 wins 1; 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-V3

  • overall performance matters — it scores 15.7 and ranks #231 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Dec 2024

Choose Llama 3.1 Nemotron 70B Instruct

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
Llama 3.1 Nemotron 70B Instruct
NVIDIA
Core performance indexes
LLM Stats Score
15.7
#231
0.4
#327
Reasoning
14.8
#230
0.1
#320
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.27 / M
— / M
Output price
$0.89 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V3
Llama 3.1 Nemotron 70B Instruct
Math
18.0#188
7.0#266
Finance
19.9#82
6.2#163
Legal
19.9#67
6.2#148
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V3 · 11 for Llama 3.1 Nemotron 70B Instruct

1 shared

DeepSeek-V3 outperforms in 1 benchmarks (MMLU), while Llama 3.1 Nemotron 70B Instruct is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

601.0B diff

DeepSeek-V3 has 601.0B more parameters than Llama 3.1 Nemotron 70B Instruct, making it 858.6% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
NVIDIA
Llama 3.1 Nemotron 70B Instruct
70.0Bparameters
671.0B
DeepSeek-V3
70.0B
Llama 3.1 Nemotron 70B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
NVIDIA
Llama 3.1 Nemotron 70B Instruct
Input- tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Llama 3.1 Nemotron 70B Instruct uses Llama 3.1 Community License.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Llama 3.1 Nemotron 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Llama 3.1 Nemotron 70B Instruct was released on 2024-10-01.

DeepSeek-V3 is 3 months newer than Llama 3.1 Nemotron 70B Instruct.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

2mo newer
Llama 3.1 Nemotron 70B Instruct

Oct 1, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron 70B Instruct has a documented knowledge cutoff of 2023-12-01, while DeepSeek-V3's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron 70B Instruct's training data extends to 2023-12-01, but cannot make a direct comparison without DeepSeek-V3's cutoff date.

DeepSeek-V3

—

Llama 3.1 Nemotron 70B Instruct

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3 and Llama 3.1 Nemotron 70B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
Llama 3.1 Nemotron 70B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V3 vs Llama 3.1 Nemotron 70B Instruct.

Which is better, DeepSeek-V3 or Llama 3.1 Nemotron 70B Instruct?

DeepSeek-V3 leads the LLM Stats Score 15.7 to 0.4. DeepSeek-V3 is made by DeepSeek and Llama 3.1 Nemotron 70B Instruct 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-V3 compare to Llama 3.1 Nemotron 70B Instruct in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Llama 3.1 Nemotron 70B Instruct scores GSM8k: 91.4%, HellaSwag: 85.6%, Winogrande: 84.5%, GSM8K Chat: 81.9%, MMLU Chat: 80.6%.

What are the context window sizes for DeepSeek-V3 and Llama 3.1 Nemotron 70B Instruct?

DeepSeek-V3 supports 131K tokens and Llama 3.1 Nemotron 70B Instruct 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-V3 and Llama 3.1 Nemotron 70B Instruct?

Key differences include LLM Stats Score (15.7 vs 0.4), licensing (MIT + Model License (Commercial use allowed) vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Llama 3.1 Nemotron 70B Instruct?

DeepSeek-V3 is developed by DeepSeek and Llama 3.1 Nemotron 70B Instruct is developed by NVIDIA.

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