Best AI for Long Context
Rankings of the best AI models for long context understanding. Compare models by context window size and long-document comprehension.
About this ranking
As of April 2026, Kimi K2.5 leads long context benchmarks with a score of 99.5, followed by Phi 4 Reasoning Plus (97.9) and Phi 4 Reasoning (97.7). Having a large context window is necessary but not sufficient — many models degrade when key information is buried in the middle of long documents.
Ranked by 53 benchmarks testing needle-in-a-haystack retrieval, multi-document QA, and long-range dependency tracking at multiple context lengths to measure degradation curves.
The context window is the maximum text a model can process in a single request, measured in tokens (~0.75 words each). A 128K window handles ~96,000 words — about the length of a novel. This leaderboard ranks models by how well they USE their context, not just how large it is.
Some models advertise 1M+ token context windows, but raw size doesn't equal quality. Many models degrade significantly after 32-64K tokens, especially for information in the middle of long documents. Check the scores above — we test at multiple lengths to measure where each model starts losing accuracy.
Models with 128K+ context windows can process a full novel or a medium-sized codebase in one request. The practical limit is whether the model actually uses the full context effectively. Top models maintain accuracy throughout; others 'forget' information in the middle of long inputs.
Yes — cost scales linearly with input tokens. Processing a 100K-token document costs 10-50x more than a 10K request, depending on the provider. Some providers offer prompt caching that reduces cost for repeated long contexts. Check per-model pricing for your typical document lengths.
Many AI models accurately recall information at the beginning and end of long inputs but miss details in the middle — the 'lost in the middle' problem. Our benchmarks specifically test this by placing key information at different positions. Models that score well on this leaderboard handle middle-of-document retrieval reliably.