Command Medium vs Mixtral 7B
Comprehensive side-by-side comparison of pricing, performance benchmarks, and capabilities
At a Glance
Best Overall Performance
Command Medium
Higher overall benchmarks
Best for Coding
Command Medium
82% coding score
Best for Reasoning
Command Medium
82.5% reasoning score
Best MMLU Score
Command Medium
83% general knowledge
Compare Different Models
Detailed Comparison
| Feature | Command Medium | Mixtral 7B | Winner |
|---|---|---|---|
| Provider | Cohere | Mistral AI | — |
| Context Window | 64k | 32k | — |
|
MMLU Score
General knowledge & reasoning | 83% | 79% | Command Medium |
|
Coding Score
Code generation & debugging | 82% | 78% | Command Medium |
|
Reasoning Score
Logic & problem-solving | 82.5% | 78.5% | Command Medium |
| Release Date | 2025 | 2025 | — |
| Vision Support | — | ✓ Yes | — |
| Function Calling | ✓ Yes | ✓ Yes | — |
Performance Comparison
MMLU (General Knowledge)
Difference: 4.0%Coding Performance
Difference: 4.0%Reasoning & Logic
Difference: 4.0%Expert Analysis
Performance Analysis
Command Medium achieves superior scores across 3 of 3 key benchmarks, including coding (82%), demonstrating stronger general capabilities.
Final Verdict
Our comprehensive recommendation based on all factors
Both models show comparable coding performance, with less than 5 points separating them on benchmark tests. Enterprise teams requiring maximum accuracy should invest in Command Medium for demanding workloads and complex tasks.
Our Recommendation
Choose Command Medium for applications where response quality directly impacts business outcomes, or evaluate both models based on your specific use case requirements.
Best For These Use Cases
Command Medium Excels At:
- Enterprise chat assistants
- Knowledge retrieval
- Document summarization
- Customer support AI
- Internal research assistance
Mixtral 7B Excels At:
- Research experiments
- Custom chatbots
- Prototype AI agents
- Educational AI
- Open-source development
Strengths & Weaknesses
Command Medium
Strengths
- • RAG integration
- • Lightweight deployment
- • Good reasoning
- • Enterprise ready
Considerations
- • Not multimodal
- • Moderate context
- • Closed-source
- • Smaller community
Mixtral 7B
Strengths
- • Open weights
- • Efficient inference
- • Fine-tuning friendly
- • Multimodal support
Considerations
- • Small context
- • Moderate reasoning
- • Not enterprise-optimized
- • Limited benchmarks
Frequently Asked Questions
Which is better: Command Medium or Mixtral 7B?
Command Medium offers superior overall performance with higher benchmark scores across MMLU, coding, and reasoning tests. The best choice depends on your specific use case requirements and performance priorities.
What are the key differences?
Command Medium leads in overall performance with higher benchmark scores, while Mixtral 7B may offer advantages in specific areas like context window size or specialized capabilities. Both models have their strengths depending on your particular needs.
Which is better for coding?
Command Medium leads in coding performance with a score of 82%, making it 4.0 percentage points ahead of Mixtral 7B. This makes Command Medium the superior choice for software development, code generation, and debugging tasks.
Can I use both models together?
Yes! Many organizations use multiple models strategically: one model for routine tasks where efficiency matters, and another for complex, mission-critical applications requiring maximum accuracy. This hybrid approach optimizes both performance and resource utilization across different use cases.
How often are these benchmarks updated?
We update all benchmark scores and pricing data daily to reflect the latest model versions and API pricing changes. Benchmark scores are sourced from official documentation, independent testing platforms like Artificial Analysis, and peer-reviewed academic evaluations. Last updated: 2/2/2026.
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