Source-tracked capacity

AI model context window rankings

Compare documented context capacity and maximum output limits across tracked models. A larger window may help a workload, but it does not prove better answers or lower cost.

Source-tracked capacity

Largest documented context windows

Context and output limits come from the model records and their specification sources. Verify endpoint, tier, and effective limits before production use.

RankModelProviderContext windowMax outputSpecs checked
1Gemini 1.5 ProGoogle2,097,1528,1922026-07-17
2GPT-5.6 LunaOpenAI1,050,000128,0002026-07-13
3GPT-5.6 SolOpenAI1,050,000128,0002026-07-13
4GPT-5.6 TerraOpenAI1,050,000128,0002026-07-13
5Gemini 1.5 FlashGoogle1,048,5768,1922026-07-17
6Gemini 2.5 FlashGoogle1,048,57665,5362026-07-13
7Gemini 2.5 Flash-LiteGoogle1,048,57665,5362026-07-13
8Gemini 2.5 ProGoogle1,048,57665,5362026-07-13
9Gemini 3 Flash PreviewGoogle1,048,57665,5362026-07-14
10Gemini 3.1 Flash-LiteGoogle1,048,57665,5362026-07-14
11Gemini 3.1 Pro PreviewGoogle1,048,57665,5362026-07-14
12Gemini 3.5 FlashGoogle1,048,57665,5362026-07-14
13Gemini 3.5 Flash-LiteGoogle1,048,57665,5362026-07-21
14Gemini 3.6 FlashGoogle1,048,57665,5362026-07-21
15Kimi K3Moonshot AI1,048,576Requires verification2026-07-17
16Claude Fable 5Anthropic1,000,000128,0002026-07-14
17Claude Mythos 5Anthropic1,000,000128,0002026-07-14
18Claude Opus 4.8Anthropic1,000,000128,0002026-07-13
19Claude Opus 5Anthropic1,000,000128,0002026-07-28
20Claude Sonnet 4.6Anthropic1,000,000128,0002026-07-13
21Claude Sonnet 5Anthropic1,000,000128,0002026-07-13
22DeepSeek V4 Flash non-thinkingDeepSeek1,000,000384,0002026-07-13
23DeepSeek V4 ProDeepSeek1,000,000384,0002026-07-13
24Grok 4.5xAI500,000Requires verification2026-07-17
25gpt-5.4-miniOpenAI400,000128,0002026-07-13
26gpt-5.4-nanoOpenAI400,000128,0002026-07-13
27Kimi K2.6Moonshot AI262,144Requires verification2026-07-17
28Kimi K2.7 CodeMoonshot AI262,144Requires verification2026-07-17
29Kimi K2.7 Code High-SpeedMoonshot AI262,144Requires verification2026-07-17
30Command ACohere256,0008,0002026-07-17
31Mistral Medium 3.5Mistral256,000Requires verification2026-07-17
32Claude Haiku 4.5Anthropic200,00064,0002026-07-13
33Gemini 3.5 Live Translate PreviewGoogle131,07265,5362026-07-14
34GPT-OSS 120B on GroqGroq131,07265,5362026-07-15
35GPT-OSS 20B on GroqGroq131,07265,5362026-07-15
36Llama 4 Scout on GroqGroq131,0728,1922026-07-15
37Qwen3-32B on GroqGroq131,07240,9602026-07-15
38Command R 08-2024Cohere128,0004,0002026-07-17
39Command R+ 08-2024Cohere128,0004,0002026-07-17
40GPT-4oOpenAI128,00016,3842026-07-13
41GPT-4o miniOpenAI128,00016,3842026-07-13

A context window is a documented capacity limit, not a guarantee that a task will use the full window well. Check the context window calculator before choosing a model.

Use the result carefully

One dimension is not a complete decision

Cost, token volume, capacity, and evidence coverage answer different questions. Compare them with a representative prompt, actual output length, retry behavior, and your quality bar.

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FAQ

Ranking methodology questions

Does a higher ranking mean a better model?

No. Each board measures one defined dimension. Token count, price, context capacity, and evidence coverage do not substitute for testing your own completed tasks.