One of the most common questions from teams building AI assistants is: which LLM should I use? The honest answer is: it depends on your volume, latency requirements, data privacy constraints, and budget. Here's a practical breakdown.
When to use GPT-4o (OpenAI)
GPT-4o is the strongest general-purpose model for instruction-following and complex reasoning. If you need the assistant to handle nuanced multi-step queries, GPT-4o is the safest choice. GPT-4o mini is significantly cheaper and handles most straightforward support queries with near-identical quality.
When to use Claude 3.5 Sonnet (Anthropic)
Claude excels at reading and reasoning over long documents. If your knowledge base contains dense legal or compliance documents, Claude's larger effective context window makes it significantly more accurate at cross-referencing information within a single conversation. It also tends to produce more cautious, consistent tone — useful for regulated industries.
When to use Gemini 1.5 Pro (Google)
Gemini is the best choice when you need image understanding alongside text. If your customers send screenshots of error messages, order confirmations, or product photos, Gemini's native multimodal capabilities process the visual input without any extra pipeline complexity.
When to use Ollama (local models)
If data privacy is a hard requirement, Ollama lets you run models like Llama 3.2 or Qwen 2.5 entirely on your own infrastructure. No API call ever leaves your environment. This is the default on the free plan — zero API key required — and the right choice for teams handling sensitive internal data.
With Ask Nexora Pro, you can switch models at any time from the LLM Models dashboard. Run different models per assistant, experiment with providers, and bring your own API key.
For most teams starting out
- Start with Ollama (free, private, no API key required).
- Switch to GPT-4o mini for higher quality with modest token cost.
- Move to Claude 3.5 Sonnet for document-heavy or compliance use cases.
- Use Gemini when your users regularly send images or screenshots.
- Use Groq's Llama 3.3 70B for high-volume, latency-sensitive deployments.