DeepSeek DeepSeek VL2 vs Meta Llama 3.1 405B Instruct

Detailed comparison for LLMs

DeepSeekMeta

On Guardion's LLM vulnerability Benchmark, Meta Llama 3.1 405B Instruct is the more secure of the two: DeepSeek VL2 scores 52.0% and Llama 3.1 405B Instruct scores 36.0% on attack success rate (ASR) (lower is better). One or both scores are estimated from public safety evaluations pending a Guardion benchmark run.

Head-to-Head Overview

Llama 3.1 405B Instruct is the overall winner in this comparison!

Attack Success Rate (lower is safer)

ASR for DeepSeek DeepSeek VL2 vs Meta Llama 3.1 405B Instruct. Green marks the safer model on each metric. Only the overall score is available for estimated models.

Overall (ASR)

DeepSeek VL2
52.0%
Llama 3.1 405B Instruct
36.0%

TAP Attack Method (ASR)

DeepSeek VL2
100.0%
Llama 3.1 405B Instruct
100.0%

Crescendo Attack Method (ASR)

DeepSeek VL2
100.0%
Llama 3.1 405B Instruct
100.0%

Zero-Shot (ASR)

DeepSeek VL2
100.0%
Llama 3.1 405B Instruct
100.0%

Key Highlights

  • Meta Llama 3.1 405B Instruct has a lower Overall (ASR).

Security Profile

Outward is better on every axis.

OverallTAPCrescendoZero-Shot
DeepSeek VL2
Llama 3.1 405B Instruct
Full security profile
DeepSeek DeepSeek VL2
Full security profile
Meta Llama 3.1 405B Instruct

Frequently asked questions

Is DeepSeek DeepSeek VL2 or Meta Llama 3.1 405B Instruct more secure?

On Guardion's LLM vulnerability Benchmark, Meta Llama 3.1 405B Instruct is the more secure of the two: DeepSeek VL2 scores 52.0% and Llama 3.1 405B Instruct scores 36.0% on attack success rate (ASR) (lower is better). One or both scores are estimated from public safety evaluations pending a Guardion benchmark run.

What is the attack success rate (ASR) of DeepSeek VL2 vs Llama 3.1 405B Instruct?

DeepSeek VL2 has a 52.0% ASR and Llama 3.1 405B Instruct has a 36.0% ASR — the share of adversarial prompts that succeed across zero-shot, TAP, and Crescendo attacks. Lower is safer.

How were DeepSeek VL2 and Llama 3.1 405B Instruct tested?

Both were red-teamed with the HarmBench framework across zero-shot, TAP (Tree of Attacks with Pruning), and Crescendo multi-turn attacks, scored by Attack Success Rate.

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