Models whose context window is at least 1,000,000 tokens (from OpenRouter's catalogue), ordered by verification score. The leaderboard doesn't test long-context recall itself. Top 15 of 37.
The best LLMs with a 1M-token context window or more
Scores come from 80 multiple-choice questions from SuperGPQA and MMLU-Pro. With that many questions, a score has a margin of error of several points, so models a few points apart are effectively tied on accuracy; the comparison pages run a significance test for any pair. To see the top two side by side, compare Claude Opus 5.5 and Gemini 4 Argon.
Speed, latency and cost are measured through OpenRouter and depend on which host serves the request; your numbers on a direct API may differ. The full procedure is on the methodology page, and the data behind this ranking can be downloaded.
What is the most accurate AI model with a million-token context window?
Claude Opus 5.5 by Anthropic: 85.0% with a 1M-token context window. Rule: Models whose context window is at least 1,000,000 tokens (from OpenRouter's catalogue), ordered by verification score. The leaderboard doesn't test long-context recall itself.
What is the runner-up?
Gemini 4 Argon by Google: 83.8% with a 1M-token context window.
Which of these costs least per correct answer?
GLM 5.3 Flash: $0.00022 per correct answer (cost per question divided by its score).