Model Benchmark Comparison
Anthropic 发布的一张图背后的数字,用原生图表重画。对照原图,研究数据,再做你自己的。
简化重绘
由我们用下面的数字重新绘制。悬停、点按或用方向键查看。这是简化重绘:它用我们自己的样式展示数字,不是原图的样子。强调色标出这张图的主角。表格里带 ~ 的是估算值。
数字
77 个点中前 10 个免费| 分组 | 系列 | 数值 | 来源 | 置信 |
|---|---|---|---|---|
| Agentic terminal coding (Terminal-Bench 2.0) | Opus 4.6 | 65.4% | 估算 | 0.97 |
| Agentic terminal coding (Terminal-Bench 2.0) | Opus 4.5 | 59.8% | 估算 | 0.97 |
| Agentic terminal coding (Terminal-Bench 2.0) | Sonnet 4.5 | 51% | 估算 | 0.97 |
| Agentic terminal coding (Terminal-Bench 2.0) | Gemini 3 Pro | 56.2% | 估算 | 0.97 |
| Agentic terminal coding (Terminal-Bench 2.0) | GPT-5 (all models) | 64.7% | 估算 | 0.97 |
| Agentic coding (SWE-bench Verified) | Opus 4.6 | 80.8% | 估算 | 0.97 |
| Agentic coding (SWE-bench Verified) | Opus 4.5 | 80.9% | 估算 | 0.97 |
| Agentic coding (SWE-bench Verified) | Sonnet 4.5 | 77.2% | 估算 | 0.97 |
| Agentic coding (SWE-bench Verified) | Gemini 3 Pro | 76.2% | 估算 | 0.97 |
| Agentic coding (SWE-bench Verified) | GPT-5 (all models) | 80% | 估算 | 0.97 |
Max 数据,目前留邮箱免费看
查看全部 77 个数据点并下载文件
这张图的完整表格、JSON、CSV 和 agent skill 文件。它们属于 Max;原型阶段,留邮箱即可解锁。
| Agentic computer use (OSWorld) | Opus 4.6 | 72.7% | 估算 | 0.97 |
|---|---|---|---|---|
| Agentic computer use (OSWorld) | Opus 4.5 | 66.3% | 估算 | 0.97 |
| Agentic computer use (OSWorld) | Sonnet 4.5 | 61.4% | 估算 | 0.97 |
| Agentic tool use (τ²-bench) Retail | Opus 4.6 | 91.9% | 估算 | 0.97 |
| Agentic tool use (τ²-bench) Retail | Opus 4.5 | 88.9% | 估算 | 0.97 |
| Agentic tool use (τ²-bench) Retail | Sonnet 4.5 | 86.2% | 估算 | 0.97 |
| Agentic tool use (τ²-bench) Retail | Gemini 3 Pro | 85.3% | 估算 | 0.97 |
| Agentic tool use (τ²-bench) Retail | GPT-5 (all models) | 82% | 估算 | 0.97 |
| Agentic tool use (τ²-bench) Telecom | Opus 4.6 | 99.3% | 估算 | 0.50 |
| Agentic tool use (τ²-bench) Telecom | Opus 4.5 | 98.2% | 估算 | 0.50 |
| Agentic tool use (τ²-bench) Telecom | Sonnet 4.5 | 98% | 估算 | 0.50 |
| Agentic tool use (τ²-bench) Telecom | Gemini 3 Pro | 98% | 估算 | 0.50 |
| Agentic tool use (τ²-bench) Telecom | GPT-5 (all models) | 98.7% | 估算 | 0.50 |
| Scaled tool use (MCP Atlas) | Opus 4.6 | 59.5% | 估算 | 0.97 |
| Scaled tool use (MCP Atlas) | Opus 4.5 | 62.3% | 估算 | 0.97 |
| Scaled tool use (MCP Atlas) | Sonnet 4.5 | 43.8% | 估算 | 0.97 |
| Scaled tool use (MCP Atlas) | Gemini 3 Pro | 54.1% | 估算 | 0.97 |
| Scaled tool use (MCP Atlas) | GPT-5 (all models) | 60.6% | 估算 | 0.97 |
| Agentic search (BrowseComp) | Opus 4.6 | 84% | 估算 | 0.97 |
| Agentic search (BrowseComp) | Opus 4.5 | 67.8% | 估算 | 0.97 |
| Agentic search (BrowseComp) | Sonnet 4.5 | 43.9% | 估算 | 0.97 |
| Agentic search (BrowseComp) | Gemini 3 Pro | 59.2% | 估算 | 0.97 |
| Agentic search (BrowseComp) | GPT-5 (all models) | 77.9% | 估算 | 0.97 |
| Multidisciplinary reasoning (Humanity's Last Exam) without tools | Opus 4.6 | 40% | 估算 | 0.97 |
| Multidisciplinary reasoning (Humanity's Last Exam) without tools | Opus 4.5 | 30.8% | 估算 | 0.97 |
| Multidisciplinary reasoning (Humanity's Last Exam) without tools | Sonnet 4.5 | 17.7% | 估算 | 0.97 |
| Multidisciplinary reasoning (Humanity's Last Exam) without tools | Gemini 3 Pro | 37.5% | 估算 | 0.97 |
| Multidisciplinary reasoning (Humanity's Last Exam) without tools | GPT-5 (all models) | 36.6% | 估算 | 0.97 |
| Multidisciplinary reasoning (Humanity's Last Exam) with tools | Opus 4.6 | 53.1% | 估算 | 0.50 |
| Multidisciplinary reasoning (Humanity's Last Exam) with tools | Opus 4.5 | 43.4% | 估算 | 0.50 |
| Multidisciplinary reasoning (Humanity's Last Exam) with tools | Sonnet 4.5 | 33.6% | 估算 | 0.50 |
| Multidisciplinary reasoning (Humanity's Last Exam) with tools | Gemini 3 Pro | 45.8% | 估算 | 0.50 |
| Multidisciplinary reasoning (Humanity's Last Exam) with tools | GPT-5 (all models) | 50% | 估算 | 0.50 |
| Agentic financial analysis (Finance Agent) | Opus 4.6 | 60.7% | 估算 | 0.97 |
| Agentic financial analysis (Finance Agent) | Opus 4.5 | 55.9% | 估算 | 0.97 |
| Agentic financial analysis (Finance Agent) | Sonnet 4.5 | 54.2% | 估算 | 0.97 |
| Agentic financial analysis (Finance Agent) | Gemini 3 Pro | 44.1% | 估算 | 0.97 |
| Agentic financial analysis (Finance Agent) | GPT-5 (all models) | 56.6% | 估算 | 0.97 |
| Office tasks (GDPval-AA EIo) | Opus 4.6 | 1606% | 估算 | 0.97 |
| Office tasks (GDPval-AA EIo) | Opus 4.5 | 1416% | 估算 | 0.97 |
| Office tasks (GDPval-AA EIo) | Sonnet 4.5 | 1277% | 估算 | 0.97 |
| Office tasks (GDPval-AA EIo) | Gemini 3 Pro | 1195% | 估算 | 0.97 |
| Office tasks (GDPval-AA EIo) | GPT-5 (all models) | 1462% | 估算 | 0.97 |
| Novel problem-solving (ARC AGI 2) | Opus 4.6 | 68.8% | 估算 | 0.50 |
| Novel problem-solving (ARC AGI 2) | Opus 4.5 | 37.6% | 估算 | 0.50 |
| Novel problem-solving (ARC AGI 2) | Sonnet 4.5 | 13.6% | 估算 | 0.50 |
| Novel problem-solving (ARC AGI 2) | Gemini 3 Pro | 45.1% | 估算 | 0.50 |
| Novel problem-solving (ARC AGI 2) | GPT-5 (all models) | 54.2% | 估算 | 0.50 |
| Graduate-level reasoning (GPQA Diamond) | Opus 4.6 | 91.3% | 估算 | 0.30 |
| Graduate-level reasoning (GPQA Diamond) | Opus 4.5 | 87% | 估算 | 0.30 |
| Graduate-level reasoning (GPQA Diamond) | Sonnet 4.5 | 83.4% | 估算 | 0.97 |
| Graduate-level reasoning (GPQA Diamond) | Gemini 3 Pro | 91.9% | 估算 | 0.30 |
| Graduate-level reasoning (GPQA Diamond) | GPT-5 (all models) | 93.2% | 估算 | 0.30 |
| Visual reasoning (MMMU Pro) without tools | Opus 4.6 | 73.9% | 估算 | 0.97 |
| Visual reasoning (MMMU Pro) without tools | Opus 4.5 | 70.6% | 估算 | 0.97 |
| Visual reasoning (MMMU Pro) without tools | Sonnet 4.5 | 63.4% | 估算 | 0.97 |
| Visual reasoning (MMMU Pro) without tools | Gemini 3 Pro | 81% | 估算 | 0.97 |
| Visual reasoning (MMMU Pro) without tools | GPT-5 (all models) | 79.5% | 估算 | 0.97 |
| Visual reasoning (MMMU Pro) with tools | Opus 4.6 | 77.3% | 估算 | 0.50 |
| Visual reasoning (MMMU Pro) with tools | Opus 4.5 | 73.9% | 估算 | 0.50 |
| Visual reasoning (MMMU Pro) with tools | Sonnet 4.5 | 68.9% | 估算 | 0.50 |
| Visual reasoning (MMMU Pro) with tools | GPT-5 (all models) | 80.4% | 估算 | 0.50 |
| Multilingual Q&A (MMMLU) | Opus 4.6 | 91.1% | 估算 | 0.97 |
| Multilingual Q&A (MMMLU) | Opus 4.5 | 90.8% | 估算 | 0.97 |
| Multilingual Q&A (MMMLU) | Sonnet 4.5 | 89.5% | 估算 | 0.97 |
| Multilingual Q&A (MMMLU) | Gemini 3 Pro | 91.8% | 估算 | 0.97 |
| Multilingual Q&A (MMMLU) | GPT-5 (all models) | 89.6% | 估算 | 0.97 |
Max 订阅者可以通过 API 取同样的数据。 API 文档
API · Max
用 API 调用这张图
Max 套餐可以取这张图的数字(每个数字都带来源),格式为 JSON 或 CSV,附重画规格;也可以让智能体通过 MCP 调用。图表 id:99900de8b864。
| 路径 | 返回 | 套餐 | |
|---|---|---|---|
| GET | /api/v1/charts/99900de8b864 | 标题、发布者、日期、图型、数据点数;用 Max 密钥时附数据链接 | 开放 |
| GET | /api/v1/charts/99900de8b864/data | 每个数据点及其来源和置信度,加上重画规格。加 ?format=csv 得到 CSV | Max |
| GET | /api/v1/charts/99900de8b864/render?view=1 | 本页使用的只读绘图视图 | 开放 |
| POST | /mcp | 工具 get_chart_data 加这个 id,供 Claude、Cursor 等智能体使用 | Max |
curl -s https://viral-chart.com/api/v1/charts/99900de8b864/data \
-H "Authorization: Bearer $VIRALCHART_KEY"claude mcp add --transport http viralchart https://viral-chart.com/mcp \
--header "Authorization: Bearer $VIRALCHART_KEY"每个密钥每分钟 60 次,超出返回 429 和 Retry-After。每个账号最多 5 个密钥,在账户页创建,只显示一次。没有 Max 时数据接口返回 402,并附套餐链接。这些数字描述的是发布者拥有的图,每个文件都带授权说明。
做一张这样的图
这张图的形式,你的数字。
实时预览。所有内容都留在你的设备上。
选择形式
简化形式:用我们自己的样式,不是原图的样子。你的数字从这张图的数据开始。
换上你的数字
这是这张图自己的名称和数字,方便你看清形式。直接改写任何名称或数字,预览会随之重画。发布前请把每一个都换成你的。
这是这张图的数字,方便你看清形式。发布前请把每一个都换成你的。
你的品牌
导出图片
免费图片的角落有一行小字 “Made with ViralChart”,别人就是通过这一行找到我们的。
Anthropic 的更多数据
全部图表数据常见问题
这些数字有多准?
它们由两遍独立读图估算得出,置信度 0.82(0 到 1)。图上印着的数字读得准,从坐标轴读出的值可能有几个百分点的偏差。
这些数据可以直接用吗?
这些数字描述的是 Anthropic 发布的图表。图片、版式和样式归他们所有。使用数字时请注明发布者,图片请用你自己的数据来做。
怎么拿到文件?
JSON、CSV 和 agent skill 文件在本页的邮箱解锁区。原型里它们是静态文件:/api/charts/99900de8b864.json 和 /api/charts/99900de8b864.skill.md。