Multi-Provider AI
Multi-Provider AI Overview
Why choose one AI when you can have them all? Somara connects you to the world's leading AI models.
Available Providers
OpenAI
- GPT-4 - Flagship model, excellent reasoning
- GPT-4 Turbo - Faster, more cost-effective
- GPT-4o - Latest multimodal model
- GPT-3.5 Turbo - Fast, economical
Anthropic
- Claude 3 Opus - Most capable, best for complex tasks
- Claude 3 Sonnet - Balanced performance/cost
- Claude 3 Haiku - Fast, affordable
- Gemini 1.5 Pro - Strong multimodal capabilities
- Gemini 1.5 Flash - Faster, cost-effective
Groq
- Llama 3.1 - Ultra-fast inference
- Mixtral - Open source, fast
Choosing the Right Model
For Complex Reasoning
- GPT-4 or Claude 3 Opus
- Best for: analysis, strategy, difficult problems
For Writing & Content
- Claude 3 Opus or Claude 3 Sonnet
- Best for: long-form content, nuanced writing
For Coding
- GPT-4 or Claude 3 Opus
- Best for: code generation, debugging, review
For Speed
- GPT-4 Turbo or Groq models
- Best for: real-time applications, high volume
For Cost Optimization
- GPT-3.5 Turbo or Claude 3 Haiku
- Best for: simple tasks, high volume
Setting Model per Assistant
- Go to Assistants
- Edit or create an assistant
- In Model Settings, select the model
- Adjust temperature and max tokens
- Save changes
Using BYOK (Bring Your Own Key)
For maximum control, use your own API keys:
Step 1: Get Your API Key
From the provider's dashboard:
- OpenAI: platform.openai.com/api-keys
- Anthropic: console.anthropic.com
- Google: aistudio.google.com
Step 2: Add to Somara
- Go to Organization Settings
- Click API Configuration
- Enter your API key for each provider
- Save settings
Step 3: Use Your Keys
When creating assistants, models using your keys will be available.
Model Comparison
Accuracy
Claude 3 Opus ≈ GPT-4 > Claude 3 Sonnet > GPT-4 Turbo
Speed
Groq > GPT-4 Turbo > Claude 3 Sonnet > GPT-4 > Claude 3 Opus
Cost (relative)
GPT-3.5 < Claude 3 Haiku < Claude 3 Sonnet < GPT-4 Turbo < GPT-4 < Claude 3 Opus
Context Window
Gemini 1.5 Pro (1M) > Claude 3 (200K) > GPT-4 (128K)
Best Practices
1. Match Model to Task
Don't use Opus for simple tasks. Don't use Haiku for complex analysis.
2. Test Multiple Models
Same prompt, different models. Find what works best.
3. Consider Latency
Real-time apps need fast models. Batch processing can use slower, more capable models.
4. Monitor Costs
Check usage analytics to optimize model selection.
5. Have a Fallback
If one provider has issues, switch to another.