Benchmark Atlas

亚洲模型实验室 · arXiv 论文

Matched-quality RL Speedup

复现 MiniMax-M1 Figure 2:除最终分数外,直接比较 CISPO 与 DAPO 达到相同性能所需的训练步数。

minimaxcisporlspeedup
RL algorithms · steps to matched quality 复现 MiniMax-M1 Figure 2:除最终分数外,直接比较 CISPO 与 DAPO 达到相同性能所需的训练步数。 示意数据,仅复现信息结构,不代表最新榜单结果。 RL algorithms · steps to matched quality MiniMax-M1 Technical Report · Figure 2 / PDF p.6 DEMO DATA 030060090012001500010203040GRPODAPOCISPO2.0× fewer stepsRL training step →AIME avg@32 ↑
Illustrative demo data · renderer: matchedQualitySpeedup

Information grammar

它如何组织信息

多算法训练轨迹 + 同分水平双向步数箭头 + 等质量 speedup 直标

Visual system
VS-68 MiniMax matched-quality speed arrow
Component ID
minimax-m1-matched-quality-speedup

Use when

适用判断

适合算法训练效率对比;匹配点必须来自同一任务、模型底座、采样与评测协议。

Figure-level evidence

Figure 2 · PDF p.6

GRPO、DAPO、CISPO 的 AIME avg@32 训练轨迹及 2x matched-quality speedup。

Verified
2026-07-12
Paper source
MiniMax-M1 Technical Report

Structured data

可替换的数据模型

示意数据,仅复现信息结构,不代表最新榜单结果。

{
  "steps": [
    0,
    100,
    200,
    300,
    400,
    500,
    600,
    700,
    800,
    900,
    1000,
    1100,
    1200,
    1300,
    1400,
    1500
  ],
  "series": [
    {
      "label": "GRPO",
      "values": [
        2,
        10,
        17,
        20,
        22,
        21,
        21,
        22,
        23,
        22,
        23,
        24,
        23,
        24,
        22,
        23
      ]
    },
    {
      "label": "DAPO",
      "values": [
        2,
        8,
        15,
        21,
        21,
        26,
        24,
        27,
        29,
        28,
        31,
        28,
        32,
        28,
        33,
        34
      ]
    },
    {
      "label": "CISPO",
      "values": [
        2,
        9,
        24,
        26,
        28,
        33,
        35,
        36,
        38,
        42,
        41,
        44,
        40,
        42,
        41,
        39
      ]
    }
  ],
  "match": {
    "score": 33,
    "candidateStep": 500,
    "referenceStep": 1000,
    "speedup": 2
  }
}

Related components

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