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
Grok-4.20 Reasoning
xAITop pickGraduate-level math and scientific reasoning
2M tokensContext - 2
Grok-4.1 Fast Reasoning
xAIProduction agent pipelines requiring accurate
2M tokensContext - 3
Grok-4 Fast Reasoning
xAIMathematical and STEM problem-solving where benchmark-level analytical depth matters
2M tokensContext - 4
Grok-4.1 Fast Non-Reasoning
xAIReal-time agentic tool-calling loops that require repeated model invocations without reasoning overhead
2M tokensContext - 5
GPT-5.4
OpenAIComplex software engineering
1.1M tokensContext - 6
Gemini 3.1 Pro Preview
GoogleComplex software engineering
1.0M tokensContext - 7
Gemini 3.5 Flash
GoogleProduction agent loops and multi-step tool-use workflows where sustained throughput matters
1.0M tokensContext - 8
DeepSeek V4 Pro
DeepSeekHigh-volume automated coding pipelines
1.0M tokensContext
Ranked by maximum context window (input tokens), largest first; ties broken by intelligence.
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.