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LLaMA 3.1 405B vs Mixtral 8x22B

Comprehensive comparison of two leading open-source AI models

LLaMA 3.1 405B

ProviderMeta
Parameters405B
KYI Score9.4/10
LicenseLLaMA 3.1 Community License

Mixtral 8x22B

ProviderMistral AI
Parameters141B (8x22B MoE)
KYI Score9/10
LicenseApache 2.0

Side-by-Side Comparison

FeatureLLaMA 3.1 405BMixtral 8x22B
ProviderMetaMistral AI
Parameters405B141B (8x22B MoE)
KYI Score9.4/109/10
Speed6/107/10
Quality10/109/10
Cost Efficiency9/108/10
LicenseLLaMA 3.1 Community LicenseApache 2.0
Context Length128K tokens64K tokens
Pricingfreefree

Performance Comparison

SpeedHigher is better
LLaMA 3.1 405B6/10
Mixtral 8x22B7/10
QualityHigher is better
LLaMA 3.1 405B10/10
Mixtral 8x22B9/10
Cost EffectivenessHigher is better
LLaMA 3.1 405B9/10
Mixtral 8x22B8/10

LLaMA 3.1 405B Strengths

  • Exceptional reasoning
  • Strong coding abilities
  • Multilingual
  • Long context window

LLaMA 3.1 405B Limitations

  • Requires significant compute
  • Large model size
  • Slower inference

Mixtral 8x22B Strengths

  • Top-tier performance
  • Efficient for size
  • Long context
  • Apache 2.0

Mixtral 8x22B Limitations

  • Requires significant resources
  • Complex deployment

Best Use Cases

LLaMA 3.1 405B

Complex reasoningCode generationResearchContent creationTranslation

Mixtral 8x22B

Complex reasoningLong document analysisCode generationResearch

Which Should You Choose?

Choose LLaMA 3.1 405B if you need exceptional reasoning and prioritize strong coding abilities.

Choose Mixtral 8x22B if you need top-tier performance and prioritize efficient for size.