- Tokens are the fundamental unit of processing in Chat GPT and determine the length and context of conversations.
- There are token limits depending on the model and account type, and exceeding them may cause the account to be blocked. IA forget parts of the conversation or show mistakes.
- ChatGPT incorporates persistent memory to remember user preferences between sessions, with management and privacy options.
- Optimizing your use of tokens and understanding their word equivalencies helps you get more complete and efficient responses.
Have you ever wondered How does ChatGPT manage the information it receives and generates during a conversation? Although we see it creating impressive texts or answering complex questions, behind it is a system that depends almost entirely on small units called TokensUnderstanding what they are, how they work, and what implications they have for using AI is essential to getting the most out of these tools, avoiding interruptions or incoherent responses, and ensuring you get the most out of every interaction.
In this article we clear up all your doubts. Questions about ChatGPT tokens, conversation recall, so-called persistent memory, and how limits can affect what you get from the model. If you've ever been stuck in the middle of an answer, been surprised by an AI that seemed to "forget" what you said, or wanted to know how to calculate how many words each token equals, you'll find all the keys here. We explain it simply, with real-life examples and helpful tips.
What are tokens in ChatGPT?
For Artificial Intelligence, texts are not processed as whole words, but as small pieces called tokens. a token It can be a complete word, part of a word, a punctuation mark, a space, and even an emoji.Everything you type in the chat and everything the model replies to is translated internally into a long sequence of these tokens, which are the true raw material on which the AI works.
Why tokens and not words? Because the model needs a standard and efficient way of splitting the text that is equally valid in all languages, allowing for the identification of very long words, prefixes, suffixes, boldface, symbols, etc. This improves accuracy and flexibility: splitting "impressive" is not the same as splitting "impressive" + "impressive" if they appear in different contexts or with spelling errors.
A simple example to understand this: the phrase “ChatGPT is useful” could be split into five tokens — “Chat”, “G”, “PT”, “is”, “useful” —. As you can see, sometimes a word is split, and other times a group of words can form a single token, depending on the segmentation created by OpenAI.
How much is each token worth? Relationship between tokens and words
The relationship between tokens and words is not exact, but there are some approximate equivalences. that will help you get an idea of how much space your message or the AI's takes up. In English, a token is usually about four characters, which is usually equivalent to three-quarters of a word.. But be careful: in Spanish and other languages, this ratio changes because words tend to be a bit longer, so each word can involve more than one token. Also, punctuation marks, emoticons and spaces count as separate tokens.
- A token: approximately 4 characters (in English) or almost a word.
- 100 tokens: between 70 and 75 English words.
- One or two sentences: usually about 30 tokens.
- An average paragraph: between 80 and 120 tokens (depending on the language and complexity).
- 1.500 words: about 2.048 tokens (about 5 pages of standard text).
- 3.000 words: around 4.096 tokens (up to 10 standard pages) Become).
- 6.000 words: about 8.192 tokens (about 21 pages).
How can you calculate the number of tokens in your text? There are several online token calculators (and, if you're using it professionally, OpenAI offers its own library), but if you just want a quick estimate, count about 3/4 words per token in English, and a little less in Spanish, or divide the number of characters by 4.
Why are tokens so important?
tokens They're not just for processing text: they're how ChatGPT and other AI models control conversation length and memory.Every message you send and every response you receive consumes a certain amount of tokens. Therefore, knowing the limits is essential: if you exceed them, the model may cut off information, forget important parts, or even display errors.
The more tokens you use, the more information the AI will manage… until the quota runs out. Limits exist primarily for:
- Ensure the model works efficiently and quickly for all users.
- Avoid blocks or slowdowns due to messages that are too long.
- Control API costs, since each token processed requires resource consumption (and, in the case of the API version, money).
Token limits depending on the ChatGPT version
The ChatGPT model has a maximum number of tokens it can handle in each conversation turn. (the sum of what you type and what the model answers). These limits vary by version:
- GPT-3 and GPT-3.5: up to 4.096 tokens per interaction (approximately 8.000 words). To better understand the differences, consult our Comparison between GPT-3.5 and GPT-4.
- GPT-4: up to 8.192 tokens of context.
- GPT-4 Turbo and its advanced variants for enterprise/API users: up to 128.000 tokens of context.
- In some experimental or developer cases, OpenAI has offered “extended” versions with up to 32.768 tokens per conversation (only to selected users).
Important: Both your question and final answer count together toward that limit. If you write a very long message, the model will have less token space available to respond to you.
What happens if I exceed the token limit?
When you approach or exceed the maximum allowed tokens in the version of ChatGPT you are using, there are mainly two consequences:
- In most cases, The system will display an error message indicating that you have exceeded the maximum lengthYou'll simply need to shorten your text or divide it into several parts.
- In long conversations, ChatGPT may start to Ignoring old parts of the conversation or "forgetting" relevant informationThis happens because, in order to respond, the AI removes less relevant tokens from the beginning of the chat, keeping the most recent and relevant ones.
- Responses may be truncated, incomplete, or contain less detail than expected.
Tip: If you notice that the AI forgets what you've told it before, it's probably because you've reached the token limit. You can ask it to summarize the conversation or open a new chat and continue from there.
Does ChatGPT have persistent memory? The evolution of AI with "memories"
Until recently, ChatGPT couldn't remember anything from one conversation to another.. That is, each chat was like starting from scratch, and the AI had no memory of its own. But recently, OpenAI has incorporated a feature called “persistent memory” to personalize your experience. ChatGPT may now voluntarily store certain data about you.
For example, if you tell it that you prefer summaries to be done in table format or that it remind you of any allergies, the AI can store that information and use it in future sessions. This, of course, marks a radical change in the user experience and opens the door to much more personalized and useful assistants.
How is this memory managed?
- You can enable or disable memory from Settings > Personalization > Memory.
- You have the option to delete specific memories from Manage memory.
- Even if you delete a conversation, the memories generated during that session may remain… unless you explicitly delete them.
In addition, there is the way to temporary conversations: Chats that don't store memories, don't appear in your history, and aren't used to train OpenAI models. Useful if you want extra privacy or simply prefer the AI not to retain any of your preferences.
How does context affect tokens and conversation recall?
El Context in ChatGPT is critical. Everything you say takes up space in the token limit, just like the answers it gives you. This way, the model can “remember” from the information provided above… until the chat becomes so long that you have to start “forgetting” the initial part.
So, if you have a long or highly technical conversation, you may notice that ChatGPT starts to become less precise, stops understanding references, or even responds incoherently. It's not an artificial memory issue, it's simply that the token limit has been reached and old parts of the chat have been displaced out of context.
In these cases, requesting regular recaps or starting a new conversation are recommended strategies to maintain relevance.
Can token usage be optimized? Strategies and tools
There are different ways to optimize token management To avoid problems and get more complete and useful answers:
- Reduce the unnecessary: Eliminate long polite phrases, repetition, or excessive greetings. Get straight to the point.
- Condenses informationIf you have a lot of text, summarize the main points first and ask ChatGPT for a concrete answer.
- Divide into parts: Send information in manageable chunks. This way, you don't overwhelm the token limit, and the AI can dig deeper into each block.
- Use calculatorsIf your text is especially long, use a token calculator to estimate how many you use and plan accordingly.
- Request intermediate summaries: This way you can compress the context and leave room for further progress.
Are there differences between models? Tokens, memory, and costs
Not all ChatGPT and other AI models work the same. Token limits depend on both the model and the configuration and platform.:
- La free version usually has lower limits.
- The API or enterprise versions can dramatically increase the number of available tokens.
- Models like GPT-4 Turbo or specialized versions allow for much longer contexts and, therefore, richer and more personalized conversations.
- Yes, Each additional token means more cost in API usage. The more tokens the model processes, the more you pay per query.
Furthermore, tokens are not always interpreted the same way: the same text can result in a different number of tokens depending on the segmentation and language. Using the model in Spanish, for example, is usually a little more "expensive" in terms of tokens than in English.
What's happening at the level of privacy and data control?
OpenAI has made it clear that may use the data you provide, including recall, to improve its models unless you disable data sharing from your data control settings.
If you are concerned about privacy, always use temporary conversations and review the settings sections related to memory and memory management.
What differentiates ChatGPT from other token management models?
The concept of context through tokens is common to almost all natural language models. However, The speed with which ChatGPT “forgets” old information, how it handles persistent memories, and the flexibility in token limits make it especially interesting. for those seeking customization and efficiency.
Other models may have narrower context limits, fewer memory customization options, or tighter control over stored data. Therefore, understanding the characteristics of each version is key.
Mastering tokens is the foundation for understanding how to interact effectively with ChatGPT, take advantage of its memory features, and avoid common conversation pitfalls.
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