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Model guide · updated 2026

Best long-context AI models (biggest context windows)

A bigger context window means more of your codebase, documents, or conversation history fits in a single prompt — no chunking, no losing the thread. These models are ranked by maximum context window.

  1. 1

    Grok-4.20 Reasoning

    xAITop pick

    Graduate-level math and scientific reasoning

    2M tokens
    Context
  2. 2

    Grok-4.1 Fast Reasoning

    xAI

    Production agent pipelines requiring accurate

    2M tokens
    Context
  3. 3

    Grok-4 Fast Reasoning

    xAI

    Mathematical and STEM problem-solving where benchmark-level analytical depth matters

    2M tokens
    Context
  4. 4

    Grok-4.1 Fast Non-Reasoning

    xAI

    Real-time agentic tool-calling loops that require repeated model invocations without reasoning overhead

    2M tokens
    Context
  5. 5

    Grok-4 Fast Non-Reasoning

    xAI

    High-throughput real-time chat where low latency and cost per token outweigh depth of reasoning

    2M tokens
    Context
  6. 6

    GPT-5.4

    OpenAI

    Complex software engineering

    1.1M tokens
    Context
  7. 7

    GPT-5.6 Sol

    OpenAI

    Handles very large documents and codebases in a single pass.

    1.1M tokens
    Context
  8. 8

    GPT-5.6 Terra

    OpenAI

    Handles very large documents and codebases in a single pass.

    1.1M tokens
    Context

Ranked by maximum context window (input tokens), largest first; ties broken by intelligence.

Compare the top picks →All models

Frequently asked questions

It is the maximum amount of text (measured in tokens) a model can consider at once — your prompt plus its own response. Bigger windows let you feed in long documents or whole codebases without splitting them up.

Roughly 750,000 words — about 10 average novels, or a large software repository. A 2M-token window roughly doubles that.

Up to a point. Models can lose accuracy on details buried in the middle of very long contexts ("lost in the middle"), so a huge window is most useful when paired with good retrieval and a capable model.