Mistral 7B
Open-weight Mistral model optimized for lightweight inference and experimental research.
Performance Benchmarks
MMLU (General Knowledge)
Measures broad knowledge across 57 subjects
Coding Performance
Code generation, debugging, and understanding
Reasoning & Logic
Complex problem-solving and analytical thinking
Overall Score: 79.0% - Good performance, solid choice for many applications
About Mistral 7B
Open-weight Mistral model optimized for lightweight inference and experimental research.
Mistral 7B is designed for open research, fine-tuning, lightweight inference, making it an ideal choice for developers and businesses looking for cost-effective AI capabilities. With a context window of 32k, it can handle moderate-sized documents and conversations.
Priced at $0.00 per million tokens, Mistral 7B offers exceptional value for high-volume applications. It's particularly well-suited for research experiments, open-source ai assistants, prototype chatbots.
Key Strengths
- Open weights
- Efficient inference
- Fine-tuning support
- Community-friendly
- Lightweight deployment
Limitations to Consider
- Smaller context
- Moderate reasoning
- Limited multimodal support
- Not enterprise-focused
- Requires fine-tuning for production
Ideal Use Cases
Mistral 7B excels in the following applications and scenarios:
Pricing & Cost Analysis
Extremely affordable for high-volume applications
💡 Cost Tip: For applications processing over 1 billion tokens monthly, consider this model offers excellent value at scale.
Quick Stats
Top Competitors
Falcon 400B
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DeepMindFrequently Asked Questions
What is Mistral 7B best used for?
Mistral 7B is specifically optimized for open research, fine-tuning, lightweight inference. It excels in research experiments, open-source ai assistants, prototype chatbots, making it ideal for both individuals and enterprises looking for reliable AI capabilities in these areas.
How much does Mistral 7B cost?
Mistral 7B is priced at $0.00 per million tokens. For typical usage of 10 million tokens per month (approximately 300,000 words), this translates to $0.00 monthly. This makes it one of the more affordable options in its category.
How does Mistral 7B compare to GPT-4?
Mistral 7B provides solid performance with a coding score of 78% and reasoning score of 79%. At $0.00 per million tokens, it's more cost-effective than GPT-4 Turbo's $10.00 pricing. See detailed comparison →
What is the context window size?
Mistral 7B has a 32k context window, which supports moderate-sized documents - approximately 24,000 words or 80 pages.
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