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Practical guides to fine-tuning, distillation, and deploying small language models.
Agent Frameworks vs a Fine-Tuned Tool-Calling Model
A framework wires tools to a model and manages state; it doesn't make the model pick the right tool. Which layer your failures actually live in, and why most systems need both.
Alternatives to the OpenAI Fine-Tuning API
The four categories of alternative, compared on where the model runs and what you own afterwards: self-hosted training libraries, managed open-weight platforms, cloud provider tuning services, and distillation platforms.
Can a Small Model Beat Its Teacher?
Yes, on narrow tasks. A 0.6B student beat a 120B teacher by 29 points and a 350M student beat the same teacher on two of three tool-calling benchmarks. The measured figures and why it happens.
Cost Per Million Tokens: Local vs API
A side-by-side of self-hosted small-model rates against per-token API pricing, and why the two figures aren't directly comparable even when both are quoted per million tokens.
Distillation vs Pruning
Pruning deletes parts of a trained network and keeps what survives; distillation trains a fresh small model on a large one's behaviour. Why published pruning pipelines end with a distillation step anyway.
Does Base Model Accuracy Predict Fine-Tuned Performance?
Across four mid-size models on seven tasks the base ranking inverted after fine-tuning: the worst zero-shot model tied for best once trained. Here are the ranks, the method, and what still transfers.
GPU Requirements and Cost for SLM Inference
Weight-size arithmetic for the distil labs student catalog alongside one measured serving benchmark (222 RPS and 7.6 GiB for a 4B model) and how a GPU-hour bill becomes a per-request price.
How Long Does Fine-Tuning Take?
Published distil labs runs land between roughly six and twelve hours end to end. Here is what those figures cover, which stage eats the clock, and what moves it.
How Many Examples Do You Actually Need to Fine-Tune a Model?
Twenty labelled examples is the documented floor and 20 to 100 the usual range. Here are the published results behind those figures and what moves the number in either direction.