LLaMA 3.1 70B vs Mixtral 8x22B
Comprehensive comparison of two leading open-source AI models
LLaMA 3.1 70B
ProviderMeta
Parameters70B
KYI Score9.1/10
LicenseLLaMA 3.1 Community License
Mixtral 8x22B
ProviderMistral AI
Parameters141B (8x22B MoE)
KYI Score9/10
LicenseApache 2.0
Side-by-Side Comparison
| Feature | LLaMA 3.1 70B | Mixtral 8x22B |
|---|---|---|
| Provider | Meta | Mistral AI |
| Parameters | 70B | 141B (8x22B MoE) |
| KYI Score | 9.1/10 | 9/10 |
| Speed | 7/10 | 7/10 |
| Quality | 9/10 | 9/10 |
| Cost Efficiency | 9/10 | 8/10 |
| License | LLaMA 3.1 Community License | Apache 2.0 |
| Context Length | 128K tokens | 64K tokens |
| Pricing | free | free |
Performance Comparison
SpeedHigher is better
LLaMA 3.1 70B7/10
Mixtral 8x22B7/10
QualityHigher is better
LLaMA 3.1 70B9/10
Mixtral 8x22B9/10
Cost EffectivenessHigher is better
LLaMA 3.1 70B9/10
Mixtral 8x22B8/10
LLaMA 3.1 70B Strengths
- ✓Great performance-to-size ratio
- ✓Production-ready
- ✓Versatile
- ✓Cost-effective
LLaMA 3.1 70B Limitations
- ✗Slightly lower quality than 405B
- ✗Still requires substantial resources
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 70B
ChatbotsContent generationCode assistanceAnalysisSummarization
Mixtral 8x22B
Complex reasoningLong document analysisCode generationResearch
Which Should You Choose?
Choose LLaMA 3.1 70B if you need great performance-to-size ratio and prioritize production-ready.
Choose Mixtral 8x22B if you need top-tier performance and prioritize efficient for size.