aimodelscompare

Monday, 17 August 2026

Reference

Glossary

The vocabulary the notes assume, defined once so the notes themselves can stay short.

Aggregate score
A single figure summarising performance across a whole benchmark. It collapses per-category behaviour, so two systems with the same aggregate can fail in completely different places.
Answer extraction
The step in a benchmark harness that pulls a gradeable answer out of free-form text. Strict and permissive extractors can rank the same systems differently.
Benchmark harness
The code around a benchmark: prompt template, sampling settings, extraction and scoring. Reported numbers are properties of the harness as much as of the system.
Blind scoring
Grading outputs with the identity of the producing system hidden, so expectations cannot leak into borderline judgements.
Ceiling effect
The condition where nearly every candidate scores near the maximum, leaving the set unable to resolve differences. The fix is harder examples, not more of the same ones.
Cold start
The first run of a request path, before any cache or processed prefix can be reused. Cold and warm timings are not comparable.
Contamination
The presence of benchmark items in the material a system was trained on, which turns part of a score into recall rather than capability.
Context window
The maximum span of tokens a single request may occupy, shared between instruction, retrieved material, conversation history and the response.
Determinism
The property of returning the same output for the same input and settings. Sampled generation is not deterministic by default, and reruns establish the noise floor.
Evaluation set
A fixed collection of inputs with a written acceptance rule, held constant so that reruns across versions remain comparable.
Holdout
Examples deliberately kept out of sight while prompts are tuned, checked only at the end to detect fitting to the visible set.
Input distribution
The statistical shape of the inputs a deployment actually receives, including lengths, languages and malformed cases. Invented examples rarely reproduce it.
Judgement rule
The written statement of what makes an output acceptable or unacceptable. If applying it twice gives different answers, it is underspecified.
Noise floor
The run-to-run variation of a single candidate on a fixed prompt. Differences smaller than it are not findings.
Open weights
Model parameters distributed so they can be run on hardware you control, which fixes the target under test and transfers the serving stack to you.
Output contract
The required shape of an answer: format, length bounds, parseability and prohibited content. Stating it before testing keeps candidates comparable.
Prefix cache
Reuse of an already-processed shared beginning of a prompt, which reduces latency and cost for repeated prefixes and distorts naive timing tests.
Quantisation
Storing weights at reduced numerical precision to lower memory and cost. It is a quality variable, not only a deployment setting.
Tail latency
The slow end of the response-time distribution, which determines timeouts and the experience of the least fortunate requests. Means conceal it.
Temperature
The sampling setting governing how much randomness enters generation. It changes the spread of outputs and therefore what a comparison measures.
Time to first token
The delay before the first piece of a response appears, dominated by input processing and felt directly in any streaming interface.
Tokenizer
The learned segmentation that turns text into the tokens a system counts and charges for. Its behaviour on code, digits and non-Latin scripts departs sharply from word counts.

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