Mistral Nemo is a state-of-the-art 12B parameter language model developed in collaboration with Nvidia.
| ✅ Availability | Yes, Mistral Nemo Instruct here |
| 🐙 Model Type | Large Language Model (LLM) |
| 🗓️ Release Date | June 2024 |
| 📅 Training Data Cut-off Date | N/A |
| 📏 Parameters (Size) | 12 billion |
| 🔢 Context Window | 128k tokens |
| 🌎 Supported Languages | Multiple |
| 📈 MMLU Score | 85.0%* |
| 🗝️ API Availability | Yes |
| 💰 Pricing (per 1M Token) | Input: $0.3, Output: $0.3 per 1M tokens |
This model excels in multilingual tasks, reasoning, and coding performance, positioning itself as an excellent choice for a wide range of applications.
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Architecture 🏗️
Mistral Nemo is built on a robust architecture that leverages 12 billion parameters. This extensive parameterization allows the model to handle complex reasoning tasks, deliver high accuracy in multilingual scenarios, and perform sophisticated coding tasks.
The model is designed to be a drop-in replacement for systems currently using Mistral 7B, ensuring easy integration and enhanced performance.
Performance 🏎️
Mistral Nemo demonstrates top-tier performance across various benchmarks. It offers state-of-the-art reasoning capabilities, world knowledge, and coding performance.
In the Massive Multitask Language Understanding (MMLU) benchmark, Mistral Nemo scores 68%, showcasing its strong performance in handling diverse and complex tasks.
Pricing 💵
Mistral Nemo's pricing is competitive, making it an attractive option for businesses looking for high-performance language models without breaking the bank.
Token Pricing
- Input Tokens: $0.30 per million tokens
- Output Tokens: $0.30 per million tokens
Example Cost Calculation
For a project requiring 10 million input tokens and 5 million output tokens, the cost calculation would be as follows:
- Input Cost: 10 million tokens x $0.30 = $3.00
- Output Cost: 5 million tokens x $0.30 = $1.50
- Total Cost: $3.00 + $1.50 = $4.50
Use Cases 🗂️
Mistral Nemo is versatile and can be utilized in various applications, including:
- Text Generation: Crafting coherent and contextually relevant text.
- Multilingual Tasks: Translating and understanding multiple languages with high accuracy.
- Code Generation: Assisting in coding tasks, including code completion and bug fixing.
Customization
Mistral Nemo can be fine-tuned to cater to specific needs, allowing developers to tailor the model's performance to their unique requirements. This customization ensures that the model can efficiently handle specialized tasks and deliver optimal results.
Comparison 📊
When compared to other models in the market, Mistral Nemo stands out due to its balance of performance and cost. It offers superior reasoning capabilities and multilingual support, making it a formidable competitor against models like GPT-3.5 and Llama 2.
Conclusion
Mistral Nemo is a powerful language model with exceptional performance in multilingual tasks, reasoning, and coding. Its competitive pricing and ease of integration make it an ideal choice for businesses and developers looking to leverage advanced AI capabilities without incurring prohibitive costs.
