English(EN) The ultimate pelican test (Opus 5.5 max)

Anthropic 的 Opus 5.5 在单提示测试中处理 640 万个 token

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-03 22:13

一位 Reddit 用户分享了他们使用 Anthropic 的 Opus 5.5 模型进行一项广泛的“鹈鹕测试”的经验。该测试涉及单个提示，消耗了大约 640 万个 token，相当于约一小时的工作量。该用户在 r/ClaudeAI 子版块的帖子详细介绍了这次大规模的 AI 交互。 AI

影响展示了先进 AI 模型在实际使用场景中的实际应用和上下文窗口限制。

排序理由用户进行的 AI 模型能力测试，并非官方发布或基准测试。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 4 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 用户进行的 AI 模型能力测试，并非官方发布或基准测试。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: model release; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

r/ClaudeAI TIER_2 English(EN) · /u/Dacadey · 2026-10-03 22:13

终极鹈鹕测试 (Opus 5.5 max)

<table> <tr><td> <a href="https://www.reddit.com/r/ClaudeAI/comments/1wwzi3q/the_ultimate_pelican_test_opus_55_max/"> <img alt="The ultimate pelican test (Opus 5.5 max)" src="https://external-preview.redd.it/Z20zdWNuM250YnRoMU_brdQSJsvG5PbRC9tNOaby4jcBRfx9EZ_iCu-_t9PQ.png?width=6…