⚖️Learn When to Use a Small Model vs a Large Model
Stop defaulting to GPT-4 for tasks a 7B model handles fine. Build a per-task decision tree across capability, latency, and cost-per-million-tokens — then route your product's tasks accordingly.
Phase 1The Hidden Axes of Model Choice
See model size as one axis among many tradeoffs
Bigger isn't safer — it's just more expensive
6 minBigger isn't safer — it's just more expensive
Tasks have ceilings — find them before paying for headroom
7 minTasks have ceilings — find them before paying for headroom
Cost per million tokens is the only number that matters at scale
7 minCost per million tokens is the only number that matters at scale
Latency is a UX feature — and small models ship it free
6 minLatency is a UX feature — and small models ship it free
Phase 2Benchmarking the Same Task Across Sizes
Benchmark the same task across three model sizes
Fifty examples beat zero — start your eval set today
7 minFifty examples beat zero — start your eval set today
Plot the curve — capability vs cost on your task
8 minPlot the curve — capability vs cost on your task
Compare within a family before crossing providers
6 minCompare within a family before crossing providers
Average accuracy lies — slice your eval by edge case
7 minAverage accuracy lies — slice your eval by edge case
Try a smaller model with a better prompt before scaling up
8 minTry a smaller model with a better prompt before scaling up
Phase 3Production Patterns: Routing, Cascades, Distillation
Apply routing, cascades, and distillation in production
Small first, escalate on fail — the cheapest routing pattern
8 minSmall first, escalate on fail — the cheapest routing pattern
Three lawyers, one expert — the cascade pattern in practice
8 minThree lawyers, one expert — the cascade pattern in practice
Distill when traffic outgrows the cost of training
8 minDistill when traffic outgrows the cost of training
When small models fail silently — and how to catch it
8 minWhen small models fail silently — and how to catch it
Phase 4Mapping Your Product to Model Sizes
Map your product's tasks to model sizes with rationale
Write a model-sizing rationale for every task in your product
8 minWrite a model-sizing rationale for every task in your product
Frequently asked questions
- When is a small LLM actually better than a large one?
- This is covered in the “Learn When to Use a Small Model vs a Large Model” learning path. Start with daily 5-minute micro-lessons that build from fundamentals to hands-on application.
- How do I benchmark a small model against GPT-4 fairly?
- This is covered in the “Learn When to Use a Small Model vs a Large Model” learning path. Start with daily 5-minute micro-lessons that build from fundamentals to hands-on application.
- What is model cascading and how does it cut costs?
- This is covered in the “Learn When to Use a Small Model vs a Large Model” learning path. Start with daily 5-minute micro-lessons that build from fundamentals to hands-on application.
- When does it make sense to distill a large model into a small one?
- This is covered in the “Learn When to Use a Small Model vs a Large Model” learning path. Start with daily 5-minute micro-lessons that build from fundamentals to hands-on application.
- How do I estimate cost per million tokens across providers?
- This is covered in the “Learn When to Use a Small Model vs a Large Model” learning path. Start with daily 5-minute micro-lessons that build from fundamentals to hands-on application.
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