Mixtral 8x22B vs Phi-3 Medium
Comprehensive comparison of two leading open-source AI models
Mixtral 8x22B
ProviderMistral AI
Parameters141B (8x22B MoE)
KYI Score9/10
LicenseApache 2.0
Phi-3 Medium
ProviderMicrosoft
Parameters14B
KYI Score8.3/10
LicenseMIT
Side-by-Side Comparison
| Feature | Mixtral 8x22B | Phi-3 Medium |
|---|---|---|
| Provider | Mistral AI | Microsoft |
| Parameters | 141B (8x22B MoE) | 14B |
| KYI Score | 9/10 | 8.3/10 |
| Speed | 7/10 | 9/10 |
| Quality | 9/10 | 7/10 |
| Cost Efficiency | 8/10 | 10/10 |
| License | Apache 2.0 | MIT |
| Context Length | 64K tokens | 128K tokens |
| Pricing | free | free |
Performance Comparison
SpeedHigher is better
Mixtral 8x22B7/10
Phi-3 Medium9/10
QualityHigher is better
Mixtral 8x22B9/10
Phi-3 Medium7/10
Cost EffectivenessHigher is better
Mixtral 8x22B8/10
Phi-3 Medium10/10
Mixtral 8x22B Strengths
- ✓Top-tier performance
- ✓Efficient for size
- ✓Long context
- ✓Apache 2.0
Mixtral 8x22B Limitations
- ✗Requires significant resources
- ✗Complex deployment
Phi-3 Medium Strengths
- ✓Excellent efficiency
- ✓MIT license
- ✓Long context
- ✓Fast
Phi-3 Medium Limitations
- ✗Lower quality than larger models
- ✗Limited capabilities
Best Use Cases
Mixtral 8x22B
Complex reasoningLong document analysisCode generationResearch
Phi-3 Medium
Edge deploymentMobile appsChatbotsCode assistance
Which Should You Choose?
Choose Mixtral 8x22B if you need top-tier performance and prioritize efficient for size.
Choose Phi-3 Medium if you need excellent efficiency and prioritize mit license.