How do we select the right LLM for our use case?
LLMs power next-gen customer experiences.
How It Works:
Compare models by size, latency, cost, and safety features; benchmark on your tasks using sample prompts and evaluate output quality, speed, and robustness.
Key Benefits:
- Tailored performance: Match model to task complexity.
- Cost efficiency: Balance inference cost vs. accuracy.
- Risk management: Choose models with fine-tuning and safety guardrails.
Real-World Use Cases:
- Customer support: Compare smaller vs. larger models for chat.
- Data analysis: Test summarization quality on financial reports.
FAQs
Are open-source LLMs viable?
How test multiple models?
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