The AI arena is free today

Open Superagent

DeepSeek-V4.1-Flash vs Llama 3.1 Nemotron 70B Instruct

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 0.4.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 0.4, ranking #13 overall.

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

Choose DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #13 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose Llama 3.1 Nemotron 70B Instruct

  • you are already invested in the NVIDIA ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Llama 3.1 Nemotron 70B Instruct
NVIDIA
Core performance indexes
LLM Stats Score
51.8
#13
0.4
#324
Reasoning
48.9
#18
0.1
#317
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Llama 3.1 Nemotron 70B Instruct
Math
35.2#43
7.0#266
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 11 for Llama 3.1 Nemotron 70B Instruct

No common benchmarks found

DeepSeek-V4.1-Flash and Llama 3.1 Nemotron 70B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

693.2B diff

DeepSeek-V4.1-Flash has 693.2B more parameters than Llama 3.1 Nemotron 70B Instruct, making it 990.3% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
NVIDIA
Llama 3.1 Nemotron 70B Instruct
70.0Bparameters
763.2B
DeepSeek-V4.1-Flash
70.0B
Llama 3.1 Nemotron 70B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
NVIDIA
Llama 3.1 Nemotron 70B Instruct
Input- tokens
Output- tokens
Wed Sep 16 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas Llama 3.1 Nemotron 70B Instruct does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Llama 3.1 Nemotron 70B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, 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-V4.1-Flash

MIT

Open weights

Llama 3.1 Nemotron 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Llama 3.1 Nemotron 70B Instruct was released on 2024-10-01.

DeepSeek-V4.1-Flash is 24 months newer than Llama 3.1 Nemotron 70B Instruct.

DeepSeek-V4.1-Flash

Sep 10, 2026

5 days ago

1.9yr 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-V4.1-Flash'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-V4.1-Flash's cutoff date.

DeepSeek-V4.1-Flash

—

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-V4.1-Flash and Llama 3.1 Nemotron 70B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Llama 3.1 Nemotron 70B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Llama 3.1 Nemotron 70B Instruct.

Which is better, DeepSeek-V4.1-Flash or Llama 3.1 Nemotron 70B Instruct?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 0.4. DeepSeek-V4.1-Flash 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-V4.1-Flash compare to Llama 3.1 Nemotron 70B Instruct in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. 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-V4.1-Flash and Llama 3.1 Nemotron 70B Instruct?

DeepSeek-V4.1-Flash supports 1.0M 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-V4.1-Flash and Llama 3.1 Nemotron 70B Instruct?

Key differences include LLM Stats Score (51.8 vs 0.4), multimodal support (yes vs no), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Llama 3.1 Nemotron 70B Instruct?

DeepSeek-V4.1-Flash is developed by DeepSeek and Llama 3.1 Nemotron 70B Instruct is developed by NVIDIA.

Related comparisons