Arcada Labs Code Categories Arena 代码能力排行榜
基于 Arcada Labs Code Categories Arena 用户匿名投票的最新AI大模型代码能力排行榜,通过 Bradley-Terry 模型对 Website、UI Component、Game Dev、Data Visualization 等代码子类别进行综合评分与排名。
榜首模型
GLM 5.2
最高得分
1352.00
模型数量
136
数据版本
2026年07月12日
数据来源: Arcada Labs
排名总表
| 排名 | 模型名称 | 得分 | 95% CI | 投票数 | 机构 | 许可证 |
|---|---|---|---|---|---|---|
| GLM 5.2Zhipu AI | 1352.00 | +/-7.9 | 8,533 | Zhipu AI | Open Source | |
GPT-5.6 SolOpenAI | 1350.00 | +/-16.8 | 1,792 | OpenAI | Proprietary | |
Claude Fable 5Anthropic | 1344.00 | +/-11.6 | 3,881 | Anthropic | Proprietary | |
| 4 | Claude Opus 4.6Anthropic | 1336.00 | +/-5.1 | 23,055 | Anthropic | Proprietary |
| 5 | Claude Opus 4.6 (thinking)Anthropic | 1330.00 | +/-5.5 | 19,041 | Anthropic | Proprietary |
| 6 | Opus 4.7Anthropic | 1330.00 | +/-5.8 | 16,847 | Anthropic | Proprietary |
| 7 | 1328.00 | +/-11.9 | 3,493 | xAI | Proprietary | |
| 8 | GLM 5.1智谱AI | 1321.00 | +/-6.6 | 12,099 | 智谱AI | Open Source |
| 9 | Kimi K2.6Moonshot AI | 1320.00 | +/-4.9 | 23,919 | Moonshot AI | Open Source |
| 10 | Claude Sonnet 4.6Anthropic | 1319.00 | +/-5.1 | 22,045 | Anthropic | Proprietary |
| 11 | GLM-5-Turbo智谱AI | 1312.00 | +/-4.7 | 27,317 | 智谱AI | Proprietary |
| 12 | MiMo-V2.5-ProXiaomi | 1312.00 | +/-7.2 | 10,020 | Xiaomi | Open Source |
| 13 | Qwen3.7 Max阿里巴巴 | 1306.00 | +/-5.8 | 16,473 | 阿里巴巴 | Proprietary |
| 14 | Kimi K2.7 CodeMoonshot AI | 1300.00 | +/-8.2 | 7,614 | Moonshot AI | Open Source |
| 15 | Gemini 3.5 FlashGoogle Deep Mind | 1297.00 | +/-5.8 | 16,254 | Google Deep Mind | Proprietary |
| 16 | MiniMax M3MiniMax | 1297.00 | +/-6.5 | 12,553 | MiniMax | Open Source |
| 17 | MiMo-V2.5Xiaomi | 1295.00 | +/-4.4 | 31,718 | Xiaomi | Open Source |
| 18 | Muse SparkFacebook AI研究实验室 | 1294.00 | +/-10.9 | 4,249 | Facebook AI研究实验室 | Proprietary |
| 19 | GPT-5.5OpenAI | 1291.00 | +/-5.9 | 15,610 | OpenAI | Proprietary |
| 20 | GLM-5智谱AI | 1288.00 | +/-3.8 | 46,436 | 智谱AI | Open Source |
| 21 | Opus 4.5Anthropic | 1284.00 | +/-4.1 | 35,670 | Anthropic | Proprietary |
| 22 | Gemini 3.1 Pro PreviewGoogle Deep Mind | 1283.00 | +/-5 | 23,843 | Google Deep Mind | Proprietary |
| 23 | DeepSeek-V4-ProDeepSeek-AI | 1281.00 | +/-5.5 | 17,824 | DeepSeek-AI | Open Source |
| 24 | Kimi K2.5 (thinking)Moonshot AI | 1279.00 | +/-4 | 39,455 | Moonshot AI | Open Source |
| 25 | Claude Opus 4.8Anthropic | 1276.00 | +/-5.9 | 15,114 | Anthropic | Proprietary |
| 26 | 1275.00 | +/-4.4 | 31,074 | MiniMaxAI | Open Source | |
| 27 | Gemini 3.1 Pro PreviewGoogle Deep Mind | 1271.00 | +/-4.2 | 35,060 | Google Deep Mind | Proprietary |
| 28 | GLM-5V-Turbo智谱AI | 1270.00 | +/-4.3 | 31,672 | 智谱AI | Proprietary |
| 29 | Nex N2 ProNex AGI | 1265.00 | +/-9.1 | 5,932 | Nex AGI | Open Source |
| 30 | Qwen 3.6 Plus Preview阿里巴巴 | 1265.00 | +/-4.7 | 26,080 | 阿里巴巴 | Proprietary |
| 31 | 1260.00 | +/-4.7 | 26,100 | xAI | Proprietary | |
| 32 | GLM-4.7智谱AI | 1258.00 | +/-3.7 | 47,633 | 智谱AI | Open Source |
| 33 | GPT-5.4 (Design Skill, Medium)OpenAI | 1254.00 | +/-7.2 | 9,880 | OpenAI | Proprietary |
| 34 | GPT-5.4 (medium)OpenAI | 1252.00 | +/-5.3 | 19,407 | OpenAI | Proprietary |
| 35 | 1249.00 | +/-6.7 | 11,504 | MiniMaxAI | Open Source | |
| 36 | DeepSeek-V4-FlashDeepSeek-AI | 1248.00 | +/-4.7 | 25,437 | DeepSeek-AI | Open Source |
| 37 | 1241.00 | +/-4.6 | 27,379 | xAI | Proprietary | |
| 38 | 1234.00 | +/-5.1 | 21,060 | xAI | Proprietary | |
| 39 | 1232.00 | +/-5.1 | 20,805 | MiniMaxAI | Open Source | |
| 40 | Gemini 3.0 FlashGoogle Deep Mind | 1231.00 | +/-10.6 | 4,414 | Google Deep Mind | Proprietary |
| 41 | Claude Sonnet 4.5Anthropic | 1225.00 | +/-3.8 | 40,900 | Anthropic | Proprietary |
| 42 | Claude Sonnet 4.5 (thinking)Anthropic | 1224.00 | +/-3.9 | 40,107 | Anthropic | Proprietary |
| 43 | GPT-5.4 (low)OpenAI | 1222.00 | +/-5 | 21,683 | OpenAI | Proprietary |
| 44 | Qwen3.5-397B-A17B阿里巴巴 | 1222.00 | +/-7.9 | 8,131 | 阿里巴巴 | Open Source |
| 45 | GLM-4.7-Flash智谱AI | 1220.00 | +/-6.6 | 11,706 | 智谱AI | Open Source |
| 46 | GPT-5.4 (None)OpenAI | 1220.00 | +/-4.8 | 24,150 | OpenAI | Proprietary |
| 47 | Claude Sonnet 3.7Anthropic | 1219.00 | +/-5.9 | 15,245 | Anthropic | Proprietary |
| 48 | DeepSeek-V3.1 (thinking)DeepSeek-AI | 1217.00 | +/-5.7 | 16,258 | DeepSeek-AI | Open Source |
| 49 | Opus 4.1 (thinking)Anthropic | 1213.00 | +/-5.8 | 15,677 | Anthropic | Proprietary |
| 50 | DeepSeek V3.2-ExpDeepSeek-AI | 1213.00 | +/-5.3 | 19,490 | DeepSeek-AI | Open Source |
| 51 | GPT-5.1 (high)OpenAI | 1213.00 | +/-5.7 | 16,057 | OpenAI | Proprietary |
| 52 | GPT-5.2 (medium)OpenAI | 1212.00 | +/-4.5 | 28,372 | OpenAI | Proprietary |
| 53 | GPT-5 (high)OpenAI | 1211.00 | +/-6.2 | 13,397 | OpenAI | Proprietary |
| 54 | GPT-5.2 (None)OpenAI | 1211.00 | +/-4.4 | 29,322 | OpenAI | Proprietary |
| 55 | Step 3.7 FlashStepFun | 1210.00 | +/-6.3 | 13,365 | StepFun | Open Source |
| 56 | Qwen3.5 Plus (0215)阿里巴巴 | 1209.00 | +/-5.3 | 19,028 | 阿里巴巴 | Proprietary |
| 57 | GLM-4.6智谱AI | 1208.00 | +/-5.6 | 16,911 | 智谱AI | Open Source |
| 58 | GPT-5.2 (low)OpenAI | 1208.00 | +/-4.6 | 25,763 | OpenAI | Proprietary |
| 59 | Opus 4.1Anthropic | 1207.00 | +/-3.9 | 40,219 | Anthropic | Proprietary |
| 60 | GLM-4.5智谱AI | 1207.00 | +/-5.2 | 19,637 | 智谱AI | Open Source |
| 61 | GPT-5 (minimal)OpenAI | 1207.00 | +/-4.2 | 33,251 | OpenAI | Proprietary |
| 62 | DeepSeek V3.2DeepSeek-AI | 1206.00 | +/-4.4 | 29,394 | DeepSeek-AI | Open Source |
| 63 | GPT-5.1 (medium)OpenAI | 1204.00 | +/-5 | 21,292 | OpenAI | Proprietary |
| 64 | Claude Opus 4Anthropic | 1203.00 | +/-5.6 | 16,669 | Anthropic | Proprietary |
| 65 | Hy3Tencent | 1199.00 | +/-20.5 | 1,202 | Tencent | Open Source |
| 66 | GPT-5.1 (low)OpenAI | 1198.00 | +/-5 | 22,160 | OpenAI | Proprietary |
| 67 | MiMo-V2-FlashXiaomi | 1198.00 | +/-4.1 | 35,857 | Xiaomi | Open Source |
| 68 | Gemini 2.5-ProGoogle Deep Mind | 1196.00 | +/-8.6 | 7,044 | Google Deep Mind | Proprietary |
| 69 | GPT-5.1 CodexOpenAI | 1193.00 | +/-16.4 | 1,807 | OpenAI | Proprietary |
| 70 | GPT-5.1 (None)OpenAI | 1193.00 | +/-4.9 | 22,273 | OpenAI | Proprietary |
| 71 | GPT-5.2 (high)OpenAI | 1192.00 | +/-10.8 | 4,167 | OpenAI | Proprietary |
| 72 | GPT-5.3 CodexOpenAI | 1187.00 | +/-5.8 | 15,761 | OpenAI | Proprietary |
| 73 | Qwen3-Coder-480B-A35B阿里巴巴 | 1185.00 | +/-16.3 | 1,958 | 阿里巴巴 | Open Source |
| 74 | Mistral Large 3MistralAI | 1184.00 | +/-4.3 | 30,837 | MistralAI | Open Source |
| 75 | Claude Sonnet 4Anthropic | 1183.00 | +/-5.5 | 17,532 | Anthropic | Proprietary |
| 76 | DeepSeek-R1-0528DeepSeek-AI | 1181.00 | +/-5.4 | 17,944 | DeepSeek-AI | Open Source |
| 77 | GLM-4.5-Air智谱AI | 1180.00 | +/-5.5 | 17,256 | 智谱AI | Open Source |
| 78 | Claude Sonnet 4 (thinking)Anthropic | 1179.00 | +/-5.7 | 16,227 | Anthropic | Proprietary |
| 79 | 1177.00 | +/-6.9 | 10,828 | MiniMaxAI | Open Source | |
| 80 | AesCoder-4BDesignFlow | 1167.00 | +/-3.9 | 40,177 | DesignFlow | Open Source |
| 81 | Mistral Medium 3.5MistralAI | 1164.00 | +/-6.8 | 11,490 | MistralAI | Open Source |
| 82 | Nemotron 3 UltraNVIDIA | 1164.00 | +/-7.6 | 9,540 | NVIDIA | Open Source |
| 83 | Mistral Medium 3.1 (2508)Mistral | 1163.00 | +/-4.5 | 28,014 | Mistral | Proprietary |
| 84 | Trinity Large ThinkingArcee AI | 1158.00 | +/-6.4 | 13,416 | Arcee AI | Open Source |
| 85 | Haiku 4.5Anthropic | 1156.00 | +/-4.1 | 36,008 | Anthropic | Proprietary |
| 86 | GPT-5-miniOpenAI | 1156.00 | +/-4 | 37,565 | OpenAI | Proprietary |
| 87 | DeepSeek-V3.1DeepSeek-AI | 1154.00 | +/-5.1 | 20,278 | DeepSeek-AI | Open Source |
| 88 | Qwen3-Max-Thinking阿里巴巴 | 1152.00 | +/-4.2 | 33,808 | 阿里巴巴 | Proprietary |
| 89 | DeepSeek-V3-0324DeepSeek-AI | 1151.00 | +/-5.3 | 19,257 | DeepSeek-AI | Open Source |
| 90 | Prime Intellect: INTELLECT-3Prime Intellect | 1149.00 | +/-4.3 | 31,884 | Prime Intellect | Open Source |
| 91 | Gemini 2.5 Flash-Preview-09-2025Google Deep Mind | 1146.00 | +/-5.3 | 19,299 | Google Deep Mind | Proprietary |
| 92 | 1143.00 | +/-4 | 37,255 | xAI | Proprietary | |
| 93 | Kimi K2 0905Moonshot AI | 1140.00 | +/-17.9 | 1,504 | Moonshot AI | Open Source |
| 94 | GPT-5.1 Codex MiniOpenAI | 1136.00 | +/-4.2 | 34,250 | OpenAI | Proprietary |
| 95 | 1135.00 | +/-4.2 | 33,898 | xAI | Proprietary | |
| 96 | 1130.00 | +/-4.3 | 31,599 | xAI | Proprietary | |
| 97 | GPT-5-NanoOpenAI | 1127.00 | +/-8.6 | 6,710 | OpenAI | Proprietary |
| 98 | Kimi K2 Turbo PreviewMoonshot AI | 1126.00 | +/-15.2 | 2,094 | Moonshot AI | Open Source |
| 99 | Gemini 2.5 Flash-Lite-Preview-09-2025Google Deep Mind | 1123.00 | +/-8.5 | 6,860 | Google Deep Mind | Proprietary |
| 100 | Gemini 3.1 Flash-Lite PreviewGoogle | 1114.00 | +/-5 | 24,146 | Proprietary | |
| 101 | Phi-3-medium 14B-previewMicrosoft Azure | 1111.00 | +/-8.9 | 6,396 | Microsoft Azure | Proprietary |
| 102 | Ministral 3 14BMistralAI | 1107.00 | +/-14.4 | 2,379 | MistralAI | Open Source |
| 103 | Gemini 2.5 FlashGoogle Deep Mind | 1101.00 | +/-8.5 | 6,960 | Google Deep Mind | Proprietary |
| 104 | v0-1.5-mdVercel | 1099.00 | +/-6.9 | 11,081 | Vercel | Proprietary |
| 105 | 1095.00 | +/-4.6 | 26,862 | xAI | Proprietary | |
| 106 | Ministral 3 8BMistralAI | 1095.00 | +/-14.3 | 2,427 | MistralAI | Open Source |
| 107 | 1093.00 | +/-4.1 | 37,909 | xAI | Proprietary | |
| 108 | Qwen3-235B-A22B-2507阿里巴巴 | 1081.00 | +/-8.6 | 6,932 | 阿里巴巴 | Open Source |
| 109 | Kimi K2Moonshot AI | 1076.00 | +/-19.4 | 1,352 | Moonshot AI | Open Source |
| 110 | Magistral Medium 1.2 (2509)Mistral | 1076.00 | +/-9.4 | 5,851 | Mistral | Proprietary |
| 111 | Qwen3-235B-A22B-Thinking-2507Alibaba | 1075.00 | +/-9.1 | 6,169 | Alibaba | Open Source |
| 112 | GPT-4.1OpenAI | 1068.00 | +/-17.3 | 1,747 | OpenAI | Proprietary |
| 113 | OpenAI o3OpenAI | 1062.00 | +/-19.5 | 1,365 | OpenAI | Proprietary |
| 114 | 1058.00 | +/-5 | 23,998 | xAI | Proprietary | |
| 115 | Devstral MediumMistralAI | 1055.00 | +/-8.6 | 7,158 | MistralAI | Proprietary |
| 116 | Ministral 3 3B (2512)Mistral | 1052.00 | +/-13.5 | 2,852 | Mistral | Open Source |
| 117 | Codestral 2508Mistral | 1049.00 | +/-8.8 | 6,745 | Mistral | Proprietary |
| 118 | Qwen3-235B-A22B阿里巴巴 | 1044.00 | +/-10.1 | 5,154 | 阿里巴巴 | Open Source |
| 119 | 1041.00 | +/-11.1 | 4,295 | xAI | Proprietary | |
| 120 | GPT-4.1 miniOpenAI | 1036.00 | +/-18.3 | 1,566 | OpenAI | Proprietary |
| 121 | Mercury 2Inception | 1033.00 | +/-10.3 | 6,814 | Inception | Proprietary |
| 122 | Magistral Small 1.2 (2509)Mistral | 1028.00 | +/-9.2 | 6,448 | Mistral | Open Source |
| 123 | OpenAI o4 - miniOpenAI | 1018.00 | +/-16.2 | 2,011 | OpenAI | Proprietary |
| 124 | Olmo 3.1 32B ThinkAllen AI | 1017.00 | +/-6.3 | 16,162 | Allen AI | Open Source |
| 125 | GPT-4.1 nanoOpenAI | 1005.00 | +/-16.9 | 1,901 | OpenAI | Proprietary |
| 126 | GPT OSS 120BOpenAI | 1005.00 | +/-10.3 | 5,268 | OpenAI | Open Source |
| 127 | Qwen3-30B-A3B阿里巴巴 | 984.00 | +/-14.6 | 2,575 | 阿里巴巴 | Open Source |
| 128 | 973.00 | +/-8.8 | 7,626 | xAI | Proprietary | |
| 129 | Llama 3.1 Nemotron Ultra 253BNVIDIA | 971.00 | +/-13.8 | 3,172 | NVIDIA | Open Source |
| 130 | Mistral-Small-3.2MistralAI | 949.00 | +/-20.8 | 1,243 | MistralAI | Open Source |
| 131 | Llama 4 MaverickFacebook AI研究实验室 | 922.00 | +/-18.4 | 1,678 | Facebook AI研究实验室 | Open Source |
| 132 | Mistral Large 2.1 (2411)Mistral | 905.00 | +/-21 | 1,317 | Mistral | Proprietary |
| 133 | GPT-4oOpenAI | 903.00 | +/-18.1 | 1,780 | OpenAI | Proprietary |
| 134 | Codestral 2 (2501)Mistral | 876.00 | +/-20.7 | 1,444 | Mistral | Open Source |
| 135 | Devstral Small 1.1MistralAI | 849.00 | +/-22.5 | 1,250 | MistralAI | Open Source |
| 136 | Llama 4 ScoutFacebook AI研究实验室 | 832.00 | +/-22.6 | 1,275 | Facebook AI研究实验室 | Open Source |
数据仅供参考,以官方来源为准。模型名称旁的链接可跳转到 DataLearner 模型详情页。
关于本榜单
本榜单数据来源于Design Arena,由 Y Combinator 支持的 Arcada Labs 开发,是专注于评测 AI 设计代码生成能力的众包匿名对战平台。
与 LMArena 评测通用文本和编程能力不同,Design Arena 的代码榜专门考察模型生成具有视觉呈现效果的前端代码的能力。平台将代码任务细分为 Website、UI 组件、游戏开发、数据可视化、SVG、Web App、移动端等多个子类别,每个子类别均有独立排行。
本页展示的是 Code Categories 综合榜,即将所有子类别的用户投票混合汇总后,统一用 Bradley-Terry 模型(类 Elo 算法)计算出的综合排名。每票等权,不对各子类别做加权处理,因此投票量较大的子类别(如 Website)对综合分数的影响更大。得分越高,代表模型在设计代码生成场景下的综合人类偏好越强。
常见问题 (FAQ)
什么是 Arcada Labs Code Categories Arena?
Arcada Labs Code Categories Arena 是专注于设计代码生成能力的匿名评测平台,覆盖 Website、UI 组件、游戏开发、数据可视化等多个代码生成子类别,并将投票汇总为综合榜单。
Arcada Code Arena 与 LMArena Coding Arena 有什么区别?
LMArena Coding Arena 主要评测通用编程能力,例如代码生成、调试和算法实现;Arcada Code Arena 专注于具有视觉呈现效果的前端设计代码,例如 HTML 页面、交互 UI、图表、SVG 和原型。
排名方法论是什么?
Arcada Labs 将各代码子类别的原始投票混合后运行 Bradley-Terry 模型。每票等权,不按子类别单独加权,因此投票量较大的子类别会对综合分数产生更大影响。
哪类模型在设计代码场景表现更好?
具备强视觉理解和前端代码生成能力的大模型通常表现更好。针对 UI 和代码生成优化的专项模型,在布局、交互和视觉细节任务上也可能有突出表现。











