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AMBER — real history,
sealed in amber, replayed

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We take real, auditable incidents and freeze them at the moment before the answer was revealed. Models must redo the work with only what was knowable then, against a rubric frozen before any output existed. The cases are never published. The scores always are.

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23 cases / 26 papersprivate library, hash-sealed
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11 result reposone per vendor × endpoint
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Updated weeklysame library, same band, public hash index
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The board right now

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Same band (high), same 23 cases, same public hash index. Five rank tiers; ties are labeled as ties.

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+ AMBER board: five rank tiers (2026-W38) +
2026-W38 · leader swe-2-max @ Devin at 18/23; a five-way tie at 17/23.
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Same score, different shape

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The nine-axis completion matrix: each cell is a face's pin-level completion. Tied totals hide completely different profiles — the matrix shows what the sum can't.

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+ Nine-axis completion matrix +
Five lanes tied at 17/23, plus doubao 16/23 and gp27b 14/23.
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Why the scores can be trusted

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Every weekly issue runs like an exam: cases sealed in advance, a clean-room sitting, per-paper wire audits, anonymized publication, and a public index anyone can re-check.

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+ How a result is produced +
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Three counterintuitive findings

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Each comes with named boundaries and counterexamples in the original writeups.

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+ Effort curves +
"Think longer ≠ score better": most families backfire at top bands; swe-2 is monotone to the top.
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+ Score vs thinking budget +
Same band, same library: output-token bills span 17× while scores differ by one case.
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+ Per-case wall clock +
A vendor's high TPS only holds on easy problems; hard ones slow the token stream down.
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Result repos

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One repo per lane (model × endpoint × band), one matrix per week, wire audits and hash cross-checks included.

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The rules

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Private side, never public: the case library, oracles, transcripts, internal case IDs and variant names.
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Public side, always checkable: scores, aggregates, verdicts, the hash index — anyone can verify the library didn't change and the scores add up.
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Historical outcomes are evidence, not the only correct answer; runtime sealing ≠ clean training data. Both warnings are printed on every issue.
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Read the method: AMBER Core Specification · public hash index · roadmap

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AMBER — 琥珀式封存的
历史回放评测

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把真实、可审计的历史事件封进琥珀,精确还原到「答案揭晓之前」,让 AI 只用当时可得的信息重做一遍。评分标准在看到任何输出之前就已冻结。题目永不公开,分数永远可查。

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23 案 / 26 卷私有题库,哈希封存
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11 个成绩仓按厂商 × 端点分仓
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每周更新同库、同档、公开哈希索引
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当前总榜

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同档(high)、同 23 案、同公开哈希索引。五个名次档,并列如实标注。

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+ AMBER 当前总榜:五个名次档(2026-W38,全库 23 案) +
2026-W38 · 榜首 swe-2-max @ Devin 18/23;#2 并列五席 17/23。
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同分 ≠ 同款

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九轴完成度矩阵:每格 = 该面全部案子的钉级完成度。同分的几家,形状完全不同——总分看不见的东西,矩阵看得见。

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+ 九轴完成度矩阵 +
五家 17/23 + doubao 16/23 + gp27b 14/23,九轴同场。
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分数凭什么可信

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每期成绩像一场考试:出卷封存、净室应考、逐卷验脑、脱敏发布、人人可核对。

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+ 一期成绩怎么炼成 +
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三个反直觉发现

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都有边界,都只代表已测家族——原文里每条都标着反例。

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+ effort 曲线 +
「想更久 ≠ 考更好」:多数家族高档反噬,swe-2 单调到底。
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+ 分数 × 思考预算 +
同档同库,输出 token 账单跨 17 倍,分差不过一案。
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+ 逐题耗时 +
厂商的高 TPS 只在简单题上成立;难题想得多,吐字当场变慢。
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成绩仓

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每条车道(模型 × 端点 × 档位)一个仓,每期一篇矩阵,验脑记录与哈希对照齐全。

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规则

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私有面永不公开:题库、oracle、transcript、内部案号与变体名。
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公开面永远可查:分数、聚合、裁决、哈希索引——任何人都能核对题集没换、分数可对。
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历史结果是证据,不是唯一正解;运行时密封 ≠ 训练数据纯净——这两条警告印在每期成绩上。
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方法全文:AMBER Core Specification · 公开哈希索引 · 路线图

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