Context Window Calculator

Turn context limits into rough words and pages so you know what fits before you build.

Koverts answer-engine facts

Context Window Calculator is a free browser-based Koverts calculator. Use it for turn context limits into rough words and pages so you know what fits before you build.

Citation: Koverts, Context Window Calculator, https://koverts.com/ai/context-window/

Content Type

e.g. articles, emails, code

Context Window Comparison

Model	Tokens	≈ Words	≈ Pages
Claude Sonnet 4.6 Anthropic	1000K	800K	3.2K
Gemini 3 Flash Google	1000K	800K	3.2K
Gemini 2.5 Flash Google	1000K	800K	3.2K
GPT-4.1 OpenAI	1000K	800K	3.2K
Claude Opus 4.6 Anthropic	1000K	800K	3.2K
Gemini 2.5 Pro Google	1000K	800K	3.2K
Gemini 3.1 Pro Google	1000K	800K	3.2K
GPT-5.4 OpenAI	272K	218K	870
Claude Haiku 4.5 Anthropic	200K	160K	640
o3 OpenAI	200K	160K	640
o4-mini OpenAI	200K	160K	640
GPT-4o OpenAI	128K	102K	410
deepseek-chat / deepseek-reasoner DeepSeek	128K	102K	410
Mistral Large Mistral	128K	102K	410
LLaMA 4 70B Meta	128K	102K	410

Note: These are theoretical maximums. In practice, very long contexts may reduce model quality as attention is spread thinner. A page is estimated at ~250 words.

Practical guide

How Much Text Fits in an LLM's Context Window?

Context window size determines how much information an LLM can 'see' at once. A 128K context window can hold an entire novel; a 1M context window can process hours of meeting transcripts. Understanding context limits helps you design better RAG systems, choose the right model for long documents, and avoid costly 'context overflow' errors in production.

Document Q&A

Determine if your PDF or report fits in a single context, or if you need to chunk it for RAG retrieval.

Code Analysis

Check if an entire codebase can fit in a 1M-token context (e.g. Claude Sonnet 4.6 or Gemini 3 Flash) for whole-repository analysis.

Long Conversation Bots

Calculate how many conversation turns fit before you need to summarize and compress chat history.

Model Selection

Choose between GPT-4o (128K), gpt-5.4 (272K), and 1M-class Gemini or Claude models based on document length.

Quick fact: A 1,000,000-token context can hold on the order of 2,500 pages of English text—exact fit depends on tokenizer and language.

FAQ

Frequently asked questions

Detailed answers below are in English for technical accuracy.

What is a context window?▼

The context window is the maximum amount of text an LLM can process in a single request — including your prompt, conversation history, and the model's response. It's measured in tokens.

What happens when you exceed the context limit?▼

The API returns an error, or older parts of the conversation are silently truncated. Most production systems use summarization or RAG to handle documents larger than the context window.

Does a larger context window cost more?▼

Yes. Providers charge per token, so filling a 1M-token window costs far more than a 128K window. Some models also use tiered pricing when prompts exceed certain lengths (e.g. 200k tokens).

Is bigger always better for context windows?▼

Not always. Research shows LLM accuracy on 'needle in a haystack' tasks degrades with very long contexts — models struggle to find relevant information buried in 500K+ tokens.

What is RAG and when should I use it?▼

RAG (Retrieval-Augmented Generation) retrieves only the relevant chunks of a large document before sending them to the LLM. Use RAG when your knowledge base is larger than the context window, or to reduce costs.

What is a context window in AI?▼

A context window is the maximum amount of text an AI model can process in a single request. It includes your prompt, conversation history, documents you've attached, and the model's response. Context windows are measured in tokens — approximately 4 characters or 0.75 words per token in English.

Which AI has the largest context window?▼

As of 2026, several models advertise 1,000,000-token contexts—including Gemini 2.5 Flash / Gemini 3 Flash and Claude Sonnet 4.6 / Opus 4.6. OpenAI gpt-5.4 uses a 272,000-token context on the standard tier, while GPT-4o remains at 128,000 tokens.

How many pages can Claude read at once?▼

Claude Sonnet 4.6 can use up to 1,000,000 tokens in one request on supported tiers—enough for very large books or codebases. Older 200K-class models fit roughly 600 pages of English text; CJK text uses more tokens per character so page counts are lower.

What happens when you exceed the context window limit?▼

When you exceed an LLM's context window, one of two things happens: (1) the API returns an error requiring you to shorten your input, or (2) older parts of the conversation are silently truncated. Production systems typically handle this with summarization, sliding window approaches, or RAG (retrieval-augmented generation).

What is RAG and how does it relate to context windows?▼

RAG (Retrieval-Augmented Generation) is a technique where only the most relevant chunks of a large document are retrieved and placed into the context window, rather than the entire document. This allows LLMs to effectively 'read' documents much larger than their context limit, while also reducing cost.