Guides

How-tos and strategic perspectives on building with small language models.

From Production Traces to a Faster, Cheaper, Accurate Model
GuideClassificationQuestion Answering

From Production Traces to a Faster, Cheaper, Accurate Model

Learn how to turn your production LLM agent traces into a compact specialist model that outperforms the original, with zero manual annotation and deployment in under 12 hours.

How SLMs Can Enable On-Device RAG - Making Industrial Machinery More Usable
GuideQuestion AnsweringOn-Prem / Edge

How SLMs Can Enable On-Device RAG - Making Industrial Machinery More Usable

Fine-tuned 1B parameter models can match the accuracy of 3B base models on domain-specific documentation, making on-device RAG viable for industrial equipment without expensive AI-optimized hardware. We tested this on a Siemens PLC manual and achieved a +16 percentage point accuracy gain through distillation.

The LLM in Your Voice Assistant Is the Latency Bottleneck. Replace It with an SLM.
GuideTool CallingOn-Prem / Edge

The LLM in Your Voice Assistant Is the Latency Bottleneck. Replace It with an SLM.

Voice assistants on cloud LLMs are slow and expensive per turn. A fine-tuned SLM is cheaper and faster per request with equal-or-better accuracy on bounded tasks: brain-stage latency drops from ~700ms to ~40ms, and per-turn cost from cloud-API rates to server-amortized pennies.

Vibe-Tuning: The Art of Fine-Tuning Small Language Models with a Prompt
GuideClassification

Vibe-Tuning: The Art of Fine-Tuning Small Language Models with a Prompt

Fine-tuning is a pain – you need datasets, ML expertise, and a stack of GPUs just to get started. Not anymore. With model vibe-tuning, you go from prompt to production-ready model without these headaches. This blog post shows you exactly how to build one, starting with just a prompt.

Train Your SLM with the distil labs Claude Skill
GuideQuestion Answering

Train Your SLM with the distil labs Claude Skill

A step-by-step walkthrough of training a Text2SQL small language model using the distil labs Claude Code skill, going from raw conversation data to a working local model in a single conversation.

distil-PII: Family of PII Redaction SLMs
GuideInformation ExtractionOn-Prem / Edge

distil-PII: Family of PII Redaction SLMs

We trained and released a family of small language models specialized for policy-aware PII redaction that dramatically outperform their pre-trained counterparts.

distil labs: Small Models, Big Wins – Using SLMs in Agentic AI
GuideClassificationQuestion AnsweringTool CallingInformation ExtractionOn-Prem / EdgeAgentic AI

distil labs: Small Models, Big Wins – Using SLMs in Agentic AI

How small language models can match or beat much larger LLMs when fine-tuned to well-scoped tasks, enabling faster, cheaper, and more private agentic AI workflows.

distil labs: Small Expert Agents from 10 Examples
GuideClassificationInformation Extraction

distil labs: Small Expert Agents from 10 Examples

An overview of how distil labs turns a prompt and a few dozen examples into a small, accurate expert agent that matches LLM-level results with models 50-400x smaller.