What is an LLM context window?

An LLM context window is the maximum amount of text (measured in tokens) that the AI can "remember" and process at one time during a single conversation or API request. It includes both your prompt and the model's response.

Which AI has the largest context window?

Gemini 1.5 Pro currently has the largest commercially available context window at 2,000,000 tokens (enough for about 1.5 million words, or 5,000 pages of text).

How many tokens is a 128k context window?

A 128k context window equals 128,000 tokens, which translates to roughly 96,000 words or a 300-page book.

Does context window include the generated response?

Yes, the context window is the total budget for both input tokens (your prompt) and output tokens (the model's generated response). If your prompt uses 120,000 tokens on a 128,000 window model, it can only output 8,000 tokens.

What happens if you exceed the context window?

The API will return an error and fail to generate a response. You must truncate your prompt, summarize earlier parts of the conversation, or switch to a model with a larger capacity.

LLM Context Window Comparison 2026 (Every Major Model)

An AI's context window is its short-term memory limit. Push past it, and the model forgets the beginning of your conversation. Today, context windows range from 8,000 tokens to a massive 2 million tokens. Here's the complete comparison for 2026.

The 2026 Context Window Leaderboard

Model	Context Limit	Avg Words	Cost to Fill 1x
Llama 4 Scout	10,000,000	~7,500,000	$1.100
Gemini 3.1 Pro	2,000,000	~1,500,000	$4.000
Gemini 3 Flash	2,000,000	~1,500,000	$1.000
Gemini 2.5 Pro	2,000,000	~1,500,000	$2.500
Gemini 1.5 Pro	2,000,000	~1,500,000	$2.500
Grok 4.20	2,000,000	~1,500,000	$2.500
Grok 4.1 Fast	2,000,000	~1,500,000	$0.400
GPT-4.1	1,047,576	~785,682	$2.095
GPT-4.1 Mini	1,047,576	~785,682	$0.419
GPT-4.1 Nano	1,047,576	~785,682	$0.105
Claude Opus 4.7	1,000,000	~750,000	$5.000
Claude Opus 4.6	1,000,000	~750,000	$5.000
Claude Sonnet 4.6	1,000,000	~750,000	$3.000
Gemini 3.1 Flash-Lite	1,000,000	~750,000	$0.250
Gemini 2.5 Flash	1,000,000	~750,000	$0.300
Gemini 2.5 Flash-Lite	1,000,000	~750,000	$0.100
Gemini 2.0 Flash	1,000,000	~750,000	$0.100
Gemini 1.5 Flash	1,000,000	~750,000	$0.075
Llama 4 Maverick	1,000,000	~750,000	$0.200
Grok 4.3	1,000,000	~750,000	$1.250
Qwen 3.7 Max	1,000,000	~750,000	$2.500
Qwen 3.5 Plus	1,000,000	~750,000	$0.500
GPT-5.4	272,000	~204,000	$0.680
GPT-5.4 Mini	272,000	~204,000	$0.204
GPT-5.4 Nano	272,000	~204,000	$0.054
GPT-5.4 Pro	272,000	~204,000	$8.160
Codestral	256,000	~192,000	$0.051
GPT-5.2	200,000	~150,000	$0.350
GPT-5.2 Pro	200,000	~150,000	$4.200
GPT-5.1	200,000	~150,000	$0.250
GPT-5	200,000	~150,000	$0.250
GPT-5 Mini	200,000	~150,000	$0.050
GPT-5 Nano	200,000	~150,000	$0.010
GPT-5 Pro	200,000	~150,000	$3.000
o1	200,000	~150,000	$3.000
o1-pro	200,000	~150,000	$30.000
o3	200,000	~150,000	$0.400
o3-pro	200,000	~150,000	$4.000
o4-mini	200,000	~150,000	$0.220
o3-mini	200,000	~150,000	$0.220
o1-mini	200,000	~150,000	$0.220
Claude Opus 4.5	200,000	~150,000	$1.000
Claude Opus 4.1	200,000	~150,000	$3.000
Claude Opus 4	200,000	~150,000	$3.000
Claude Sonnet 4.5	200,000	~150,000	$0.600
Claude Sonnet 4	200,000	~150,000	$0.600
Claude Sonnet 3.7	200,000	~150,000	$0.600
Claude Haiku 4.5	200,000	~150,000	$0.200
Claude Haiku 3.5	200,000	~150,000	$0.160
Claude Opus 3	200,000	~150,000	$3.000
Claude Haiku 3	200,000	~150,000	$0.050
Sonar Pro	200,000	~150,000	$0.600
LLaMA 3.3 70B	131,072	~98,304	$0.077
Qwen 2.5 72B	131,072	~98,304	$0.030
GPT-4o	128,000	~96,000	$0.320
GPT-4o Mini	128,000	~96,000	$0.019
DeepSeek V3	128,000	~96,000	$0.036
DeepSeek R1	128,000	~96,000	$0.070
Mistral Large 3	128,000	~96,000	$0.256
Pixtral Large	128,000	~96,000	$0.256
Ministral 8B	128,000	~96,000	$0.013
Ministral 3B	128,000	~96,000	$0.005
Mistral Nemo	128,000	~96,000	$0.019
Pixtral 12B	128,000	~96,000	$0.019
Sonar Large	127,000	~95,250	$0.127
Sonar Small	127,000	~95,250	$0.025
Sonar Huge	127,000	~95,250	$0.635
Mistral Small 3	32,000	~24,000	$0.003
GPT-3.5 Turbo	16,385	~12,289	$0.008

What Actually Fits in a Context Window?

To understand these limits practically, let's translate tokens into real-world document sizes. As a general rule of thumb, 1 token ≈ 0.75 words in English. Use our token calculator for exact measurements.

4,000 tokens: A long blog post or short essay (~3,000 words).
32,000 tokens: A short academic paper or an average business report (~24,000 words).
128,000 tokens (GPT-4o, DeepSeek V3): A 300-page book like “Harry Potter and the Sorcerer's Stone” (~96,000 words).
200,000 tokens (Claude Sonnet 4.6): A very long novel or extensive codebase codebase (~150,000 words).
2,000,000 tokens (Gemini 1.5 Pro): The entire Lord of the Rings series plus the Hobbit, or an enormous monorepo codebase (~1,500,000 words).

The "Cost to Fill" Problem

While large context windows like Gemini's 2M tokens sound incredible, there is a catch: cost. API providers bill per token processed.

If you dump a 1 million token document into GPT-4 Turbo ($10/1M input tokens), that single query costs $10.00. If you ask 10 follow-up questions in the same conversation, the entire 1M token history is re-processed each time, costing another $10.00 per question. A short conversation can quickly cost over $100.

How to Manage Context Effectively

1. Retrieval-Augmented Generation (RAG)

Instead of giving the model the entire 500-page document, use a vector database to search the document mathematically. Find the 3 most relevant pages, and put only those pages in the context window. This reduces costs by 99% and often improves accuracy.

2. Prompt Caching

If you must use a massive context window (like a large codebase), look for models that support prompt caching (like Claude Sonnet 4.6). Once the large document is processed once, subsequent requests using the same prefix get massive discounts (up to 90%).

3. "Lost in the Middle" Phenomenon

Research shows that even models with 128K+ windows struggle to retrieve information placed exactly in the middle of a massive block of text. They are great at remembering the beginning and the end. If you have critical instructions, place them at the very end of your prompt.

📚 Related Tools:

Text to Token Calculator — Test if your text fits.
LLM Pricing Index — Compare API costs.

LLM Context Window Comparison (2026)