[ Free tool · 90 s ]

LLM model selector by use case

Answer 5 questions and know which model to pick (Claude, GPT, Gemini, Llama, Mistral) and why. Vendor-neutral.

Main task the model will perform
Pick the one that matters most
01 · TASK
Expected monthly volume
Total model calls
02 · VOLUME
Can data flow through a public API?
Anthropic API, OpenAI API, etc.
03 · APIOK
Latency critical?
How long can you wait for a response
04 · LATENCY
Model budget
Cost vs quality priority
05 · BUDGET

How to pick an LLM wisely.

  • Data restrictions come first · if regulated, on-premise open-source, no exceptions
  • Tier models by difficulty · Haiku/Flash for 70 % + Opus/GPT for the hard steps = -60 % cost
  • Quality matters where it matters · Don't pay Opus 5 to classify spam
  • Optimise latency via architecture · Streaming, prompt caching, batching
  • There's no universal "best model" — depends on task, volume and constraints
  • Public rankings (Chatbot Arena) don't always reflect your specific case
  • Switching models should be weeks of work, not months (portable architecture)
  • Re-evaluate every 6-12 months — market moves fast
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