Free tool

# Context Window Comparison: How Much Fits?

> Compare AI model context windows in tokens, pages and novels. See which ranked models accept a million tokens or more.
- Canonical page: https://noometry.com/tools/context-window
- Last updated: 2026-10-10
- Title: Context Window Comparison: How Much Fits? | Noometry

GPT-6 Astra accepts 1.05M tokens, about 1,575 pages of text.

Last verified October 10, 2026

Largest context windows among ranked models (thousands of tokens)

1.  GPT-6 Astra 1,050K
2.  GPT-6.1 Sol 1,050K
3.  GPT-5.6 Sol 1,050K
4.  GPT-5.5 Pro 1,050K
5.  GPT-5.5 1,050K
6.  GPT-6 Sol 1,050K
7.  GPT-5.4 1,050K
8.  GPT-5.6 Terra 1,050K
9.  GPT-5.4 Pro 1,050K
10.  GPT-5.6 Luna 1,050K
11.  GPT-6 Luna 1,050K
12.  Gemini 3.8 Flash 1,049K
13.  Gemini 3.7 Flash 1,049K
14.  Kimi K3 1,049K
15.  Gemini 3.1 Pro Preview 1,049K
16.  10401050

| Model | Context | ≈ Pages | ≈ Novels | Max output |
| --- | --- | --- | --- | --- |
| [GPT-6 Astra](https://noometry.com/models/gpt-6-astra) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-6.1 Sol](https://noometry.com/models/gpt-6-1-sol) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.5 Pro](https://noometry.com/models/gpt-5-5-pro) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.5](https://noometry.com/models/gpt-5-5) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-6 Sol](https://noometry.com/models/gpt-6-sol) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.4](https://noometry.com/models/gpt-5-4) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.6 Terra](https://noometry.com/models/gpt-5-6-terra) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.4 Pro](https://noometry.com/models/gpt-5-4-pro) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-5.6 Luna](https://noometry.com/models/gpt-5-6-luna) | 1.05M | 1,575 | 8.8 | 128K |
| [GPT-6 Luna](https://noometry.com/models/gpt-6-luna) | 1.05M | 1,575 | 8.8 | 128K |
| [Gemini 3.8 Flash](https://noometry.com/models/gemini-3-8-flash) | 1.05M | 1,573 | 8.7 | 66K |
| [Gemini 3.7 Flash](https://noometry.com/models/gemini-3-7-flash) | 1.05M | 1,573 | 8.7 | 66K |
| [Kimi K3](https://noometry.com/models/kimi-k3) | 1.05M | 1,573 | 8.7 | 1.05M |
| [Gemini 3.1 Pro Preview](https://noometry.com/models/gemini-3-1-pro-preview) | 1.05M | 1,573 | 8.7 | 66K |
| [Muse Spark 1.3](https://noometry.com/models/muse-spark-1-3) | 1.05M | 1,573 | 8.7 | 131K |
| [Gemini 3.5 Flash](https://noometry.com/models/gemini-3-5-flash) | 1.05M | 1,573 | 8.7 | 66K |
| [Gemini 3.6 Flash](https://noometry.com/models/gemini-3-6-flash) | 1.05M | 1,573 | 8.7 | 66K |
| [Gemini 3 Flash Preview](https://noometry.com/models/gemini-3-flash-preview) | 1.05M | 1,573 | 8.7 | 66K |
| [Muse Spark 1.2](https://noometry.com/models/muse-spark-1-2) | 1.05M | 1,573 | 8.7 | 131K |
| [MiMo-V2.6-Pro](https://noometry.com/models/mimo-v2-6-pro) | 1.05M | 1,573 | 8.7 | 131K |
| [Muse Spark 1.1](https://noometry.com/models/muse-spark-1-1) | 1.05M | 1,573 | 8.7 | 131K |
| [MiMo-V2.6-Flash](https://noometry.com/models/mimo-v2-6-flash) | 1.05M | 1,573 | 8.7 | 131K |
| [Hy4 preview](https://noometry.com/models/hy4-preview) | 1.05M | 1,573 | 8.7 | 64K |
| [MiMo-V2.5-Pro](https://noometry.com/models/mimo-v2-5-pro) | 1.05M | 1,573 | 8.7 | 131K |
| [Gemini 2.5 Pro](https://noometry.com/models/gemini-2-5-pro) | 1.05M | 1,573 | 8.7 | 66K |
| [MiMo-V2.5](https://noometry.com/models/mimo-v2-5) | 1.05M | 1,573 | 8.7 | 131K |
| [Mistral Large 4](https://noometry.com/models/mistral-large-4) | 1.05M | 1,573 | 8.7 | 262K |
| [MiMo-V2-Pro](https://noometry.com/models/mimo-v2-pro) | 1.05M | 1,573 | 8.7 | 131K |
| [Gemini 3.5 Flash Lite](https://noometry.com/models/gemini-3-5-flash-lite) | 1.05M | 1,573 | 8.7 | 66K |
| [Gemini 3.1 Flash Lite](https://noometry.com/models/gemini-3-1-flash-lite) | 1.05M | 1,573 | 8.7 | 66K |
| [Gemini 2.5 Flash](https://noometry.com/models/gemini-2-5-flash) | 1.05M | 1,573 | 8.7 | 66K |
| [Gemini 2.5 Flash-Lite](https://noometry.com/models/gemini-2-5-flash-lite) | 1.05M | 1,573 | 8.7 | 66K |
| [GPT-4.1](https://noometry.com/models/gpt-4-1) | 1.05M | 1,571 | 8.7 | 33K |
| [GPT-4.1 mini](https://noometry.com/models/gpt-4-1-mini) | 1.05M | 1,571 | 8.7 | 33K |
| [GPT-4.1 nano](https://noometry.com/models/gpt-4-1-nano) | 1.05M | 1,571 | 8.7 | 33K |
| [Step 5 Preview](https://noometry.com/models/step-5-preview) | 1.02M | 1,536 | 8.5 | 66K |
| [Claude Fable 5.1](https://noometry.com/models/claude-fable-5-1) | 1M | 1,500 | 8.3 | 128K |
| [Claude Opus 5.5](https://noometry.com/models/claude-opus-5-5) | 1M | 1,500 | 8.3 | 128K |
| [Claude Opus 5](https://noometry.com/models/claude-opus-5) | 1M | 1,500 | 8.3 | 128K |

[See which models actually use long context well →](https://noometry.com/best/long-context)

## Frequently asked questions

### Which AI model has the largest context window?

GPT-6 Astra accepts 1.05M tokens, about 1,575 pages of text.

### Does a bigger context window mean better answers on long documents?

No. Many models lose accuracy well before their limit. Check the long-context category ranking, which measures how well models actually use long inputs.