Everything about ai-inference
19 connected nodes across dictionary, workflows, comparisons, prompts, tool stacks and use cases.
Small Language Model (SLM)
A language model with roughly 1–15B parameters, small enough to run on a laptop, phone or single GPU while handling narrow tasks well.
Local LLM
A language model run on your own machine or server instead of a cloud API, so prompts and data never leave your infrastructure.
Reasoning Model
An LLM trained to spend extra compute thinking through a problem internally before answering, improving accuracy on math, code and planning.
Prompt Caching
Reusing the processed form of a repeated prompt prefix so later requests are cheaper and faster.
Semantic Cache
A cache that returns a stored LLM answer when a new question means the same thing as an earlier one, even if worded differently.
LLM Gateway
A proxy between your app and model providers that centralises keys, routing, fallbacks, logging and spend limits.
Knowledge Distillation
Training a small model to imitate the outputs of a large one, keeping most of the quality on a target task at a fraction of the cost.
AI Red Teaming
Deliberately attacking an AI system — jailbreaks, prompt injection, data leaks — to find failures before real users do.
Run an LLM Locally
Set up a private, offline language model on your own computer in under an hour.
Cut LLM Inference Costs
A step-by-step method to reduce model spend without degrading output quality.
Route Requests Between Models
Send each request to the cheapest model that can handle it, escalating only when needed.
Red Team an AI App
A repeatable process for attacking your own AI product before launch.
Local LLM vs Cloud API
Local models win on privacy and fixed cost; cloud APIs win on quality, scale and zero maintenance.
Reasoning Model vs Standard LLM
Reasoning models are more accurate on multi-step problems but slower and pricier; standard calls suit simple, fast tasks.
Model Routing Classifier Prompt
A cheap-model prompt that labels request difficulty so it can be routed to the right model.
Red Team Attack Plan Prompt
Generates a tailored list of adversarial tests for your own AI feature.
Local AI Stack
Open-source tools to run chat, retrieval and agents entirely on your own hardware.
LLM Cost Optimization Stack
The layers that keep AI spend predictable as usage grows.