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LLaMA 3.1 405B vs Mixtral 8x7B

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 8x7B

ProviderMistral AI
Parameters46.7B (8x7B MoE)
KYI Score8.7/10
LicenseApache 2.0

Side-by-Side Comparison

FeatureLLaMA 3.1 405BMixtral 8x7B
ProviderMetaMistral AI
Parameters405B46.7B (8x7B MoE)
KYI Score9.4/108.7/10
Speed6/108/10
Quality10/108/10
Cost Efficiency9/109/10
LicenseLLaMA 3.1 Community LicenseApache 2.0
Context Length128K tokens32K tokens
Pricingfreefree

Performance Comparison

SpeedHigher is better
LLaMA 3.1 405B6/10
Mixtral 8x7B8/10
QualityHigher is better
LLaMA 3.1 405B10/10
Mixtral 8x7B8/10
Cost EffectivenessHigher is better
LLaMA 3.1 405B9/10
Mixtral 8x7B9/10

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 8x7B Strengths

  • Excellent speed-quality balance
  • Efficient architecture
  • Strong multilingual
  • Apache 2.0 license

Mixtral 8x7B Limitations

  • Smaller context than LLaMA 3.1
  • Complex architecture

Best Use Cases

LLaMA 3.1 405B

Complex reasoningCode generationResearchContent creationTranslation

Mixtral 8x7B

Code generationMultilingual tasksReasoningContent creation

Which Should You Choose?

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

Choose Mixtral 8x7B if you need excellent speed-quality balance and prioritize efficient architecture.