LLM (large language model)
A large language model, or LLM, is a neural network trained on very large amounts of text to predict which piece of text comes next. By repeating that prediction one piece at a time, it can answer questions, write, translate, summarize and produce code.
Last updated November 8, 2026
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Your message passes through without being written down; your chats are only ever stored encrypted.
The model doesn’t know you.
It gets the question, never your email, your account or your IP address.
Nothing is left along the way.
The reply comes back and is stored here, encrypted; even when you sync, your key never reaches us in the clear.
How it works
An LLM does not look answers up in a database. During training it adjusts billions of numerical weights so that, given a stretch of text, it assigns a high probability to the words that plausibly follow. When you chat with one, your message and the earlier conversation are cut into tokens, the model computes the probability of the next token, picks one, adds it to the text and starts again until the reply is finished.
Two phases shape the result. Pre-training on a vast corpus teaches the model grammar, facts and styles of writing. Fine-tuning then steers it toward being a helpful assistant, often with human feedback, and that second phase is also where a maker decides what the model should decline to do. Two models with the same size can therefore behave very differently.
Size and design matter, but they are not everything. A larger model usually knows more and reasons better, a smaller one answers faster and costs less, and some models are built to think step by step before they reply. Because an LLM produces plausible text rather than verified facts, it can be wrong with confidence, which is why important claims deserve a second look.
In NeverNo
NeverNo is a place to use many LLMs side by side. The model picker lists open models that NeverNo runs on providers chosen for not keeping requests, such as DeepSeek, GLM, Qwen, Mistral and NeverNo Uncensored, and shows them as private. Claude, GPT, Gemini and Grok are reached anonymized: their makers read the text without knowing who you are, and their own rules still apply.
You can switch model in the middle of a conversation, compare answers, or leave the choice to Auto. Each model page on the site gives its maker, context window, price in credits and the figures we measured ourselves. Changing engine never means starting over: the conversation is kept encrypted in your browser, whichever model produced each reply.
Worth remembering
An LLM predicts the next token; everything else, from translation to code, comes out of that one skill.
Training teaches it knowledge and style, fine-tuning shapes its behavior, and the maker's choices decide what it declines.
Fluent does not mean true: check facts that matter.
Context window, speed, price and willingness to answer all differ from one model to the next, so the best model depends on the task.
The next token is drawn from a ranked list of candidates, so asking twice can produce two differently worded answers, both plausible.
Frequently asked questions
Is an LLM the same thing as ChatGPT?
No. ChatGPT is an app built by OpenAI on top of its own LLMs. The LLM is the engine; the chat window, the memory and the settings around it make up the product. NeverNo is another such app and lets you pick among many engines.
Does an LLM understand what it writes?
It models patterns of language very well and can follow instructions and reason through problems, but it has no direct access to the world. It can state something false in a convincing tone, an effect called hallucination.
How do I choose a model on NeverNo?
Start with Auto or with a fast free model for everyday questions, and move to a larger or reasoning model for hard problems, long documents or careful writing. The model pages list context, price and measured figures to help you compare.
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