Glossary

Agent
A model given tools and a goal, left to loop — deciding what to do next and doing it — until the job is done or it gives up.
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Agent loop
Plan, call a tool, read the result, decide again. The cycle an agent repeats until it finishes or is stopped.
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AI21
An Israeli lab behind the Jamba models, built for very long inputs.
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Alibaba
Publishes the Qwen models, a large open-weight family covering text, images and code.
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Amazon
Builds the Nova models and resells most other vendors’ through Bedrock, its managed model service.
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Anthropic
The company behind the Claude models. Publishes the most complete pricing of any vendor read here, including what writing to the cache.
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ByteDance
TikTok’s parent company, which publishes the Doubao and Seed models.
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Cache write
The charge for putting a prefix into the prompt cache. Usually more than the input rate, not less.
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Chain of thought
Asking a model to work through its reasoning before answering, which measurably improves accuracy on multi-step problems.
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ChatGPT
OpenAI’s chat assistant, on the web, desktop and phone. The usual first encounter with a large language model.
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Claude
Anthropic’s assistant, on the web, desktop and phone.
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Claude Code
Anthropic’s coding agent, run in a terminal or inside an editor. It reads and edits a whole repository rather than one file.
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Codex
OpenAI’s coding agent, run from the terminal or delegated to in the cloud.
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Cohere
A Canadian company selling models aimed at business use, particularly search and retrieval over a company’s own documents.
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Computer use
A model driving a screen directly — looking at pixels, moving a cursor, typing — instead of calling an API.
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Context rot
The tendency of a model to attend less to material buried in the middle of a long context than to its start or end.
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Context window
The total tokens a model can consider at once: your prompt, the conversation so far, and the answer it is writing.
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Copilot
Microsoft’s assistant brand. GitHub Copilot writes code in an editor; Microsoft 365 Copilot sits inside Word, Excel, Outlook and Teams.
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DeepSeek
A Chinese lab whose models are notably cheap per token and published as open weights, which is why they turn up in so many cost comparisons.
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Embedding
A list of numbers representing a piece of text, arranged so that similar meanings land near each other.
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Evals
A repeatable test set you score a model against, so a change can be shown to help rather than assumed to.
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Few-shot prompting
Showing the model two or three worked examples of what you want, instead of describing it.
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Fine-tuning
Continuing training on a smaller, curated set of examples to specialise a model or teach it a format.
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Frontier model
The largest and most capable model a vendor currently offers, priced accordingly.
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Gemini
Google’s assistant, on the web and phone and woven through Workspace — Docs, Gmail and Sheets.
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Google
The company behind the Gemini models, sold through Google AI Studio and Vertex AI.
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Grok
xAI’s assistant, reached on its own site and inside X.
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Hallucination
A fluent, confident, entirely invented answer. The failure mode that matters, because it looks exactly like a correct one.
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Inference
Running a trained model to get an answer. Everything you pay for by the token is inference, not training.
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Knowledge cutoff
The date after which a model saw no training data. It knows nothing later unless you tell it or it can search.
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Large language model
A model trained to predict the next token over enormous amounts of text, which turns out to be enough to do a great deal.
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Le Chat
Mistral’s assistant, on the web and phone.
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Llama
Meta’s family of open-weight models. Free to download and run on your own machine; several hosting companies also sell access by the token.
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Meta
The company behind the Llama models, which it publishes as open weights you can download and run yourself.
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Microsoft
Sells other companies’ models through Azure alongside its own smaller Phi models, and puts them behind the Copilot name across Windows and.
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MiniMax
A Chinese lab whose models cover text, speech and video.
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Mistral AI
A French lab publishing both open-weight and paid models, and the usual answer when a project has to stay inside Europe.
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Model Context Protocol
An open standard for connecting models to tools and data, so one integration works across many applications.
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Moonshot AI
A Chinese lab behind the Kimi models, known for very large context windows.
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Multimodal
A model that accepts more than text — images, audio or video — in the same prompt.
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Open weights
A model whose trained parameters are published, so anyone can run it on their own hardware.
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OpenAI
The company behind the GPT models and ChatGPT. Sells access through its own API and through Microsoft Azure.
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Per million tokens
How model prices are quoted: dollars per million tokens, charged separately for what you send and what comes back.
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Pretraining
The first and most expensive stage: learning to predict the next token across a very large body of text.
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Prompt
Everything you send the model on one call: instructions, context, history and question together.
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Prompt caching
Paying a reduced rate for a prefix the vendor has already processed, instead of full price for sending it again.
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Rate limit
A cap on how much you may send in a window, usually counted in requests and tokens per minute.
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Reasoning model
A model trained to produce a long internal working-out before its answer. More accurate on hard problems, slower and dearer.
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Reinforcement learning from human feedback
Training a model against human judgements of which answer is better, rather than against a single correct answer.
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Retrieval-augmented generation
Looking up relevant documents and putting them in the prompt, so the model reads facts rather than recalling them.
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System prompt
Standing instructions sent ahead of every conversation, setting the role, rules and format.
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Temperature
How much randomness to allow when picking each token. Low is repeatable and dull; high is varied and unreliable.
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Token
The unit a model reads and writes. Roughly three quarters of an English word, so 1,000 tokens is about 750 words.
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Tokenizer
The fixed table that chops text into tokens. Decided before training and never changed afterwards.
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Tool use
Letting a model call functions you define — search, read a file, send a request — and read back what they return.
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Vibe coding
Building software by describing what you want and iterating on what the model produces, rather than writing it line by line.
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xAI
The company behind the Grok models.
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Zhipu AI
A Chinese lab behind the GLM models.
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xAI

The company behind the Grok models.

You most often meet it as Grok.

Reached through an API you call from your own code and a chat app you open in a browser or on a phone.

What its models cost, and which of them suits a given job, is on Model usage. Prices there are read from this vendor’s own published page and carry the date they were read.

Official site: https://x.ai/

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