Amazon Nova
- Focus on Practicality: Real-world applications for balance of accuracy, speed, and cost-effectiveness
- Multimodal Capabilities: Strong across data types
- Cost-Effectiveness: models that are affordable and highly performant
- Weakness: new model and full performance benchmarks are yet to be determined
- When to use: priority for practical applications, cost-effective, and strong multi-modal capabilities in Amazon ecosystem
Llama
- Open Source: useful for research and innovation as a way to access and build upon the model
- Strong Performance: consistently high performance across benchmarks
- Large Community: growing community of users and contributors and has been used across applications
- Weakness: potential for misuse for generating harmful content and malicious activities
- When to use: open source, balance of performance and accessibility, extensible
Mistral
- High Performance: Strong benchmarks and beating many competitor models
- Focus on Safety: Strong emphasis on safety and bias mitigation
- Efficiency: performance with efficiency in computational resources
- Weakness: full performance benchmarks are yet to be determined
- When to use: high performance, safety, and efficiency
Gemini
- Advanced Capabilities: cutting-edge capabilities in reasoning, code generation, and multimodal understanding
- Strong Backing: support from Google that provides significant dedicated resources and expertise
- Weakness: only available through Google services, limited accessibility and flexibility for independent developers and researchers, tends to be prone to gaps in hallucinated responses, threads of related responses are brittle
- When to use: advanced capabilities within a Google ecosystem of services
DeepSeek
- High Performance: state-of-the-art performance on benchmarks and surpassing many proprietary models
- Open source: Built with an open community in mind for continuous innovation and development
- Focus on Reasoning: strong in reasoning tasks, understanding, and solving complex problems
- Weakness: relatively new model and full performance benchmarks are yet to be determined
- When to use: open source, high performance, strong reasoning, extensible
