{"id":302,"date":"2026-06-15T08:14:52","date_gmt":"2026-06-15T00:14:52","guid":{"rendered":"https:\/\/aidashxp.com\/mimo-code-review\/"},"modified":"2026-06-15T08:14:52","modified_gmt":"2026-06-15T00:14:52","slug":"mimo-code-review","status":"publish","type":"post","link":"https:\/\/aidashxp.com\/en\/mimo-code-review\/","title":{"rendered":"Xiaomi MiMo Code in-depth review: open source AI programming agent, long-term task memory ability surpasses Claude Code"},"content":{"rendered":"<p class=\"wp-block-paragraph\">Xiaomi MiMo team officially open sourced on June 10<strong>MiMo Code V0.1.0<\/strong>\u2014\u2014A terminal AI programming agent built based on OpenCode.<a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Code, and for the first time integrates persistent project memory, multi-agent collaboration and voice programming into an MIT open source license tool.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">core competencies<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The core architecture of MiMo Code is built around the three pillars of \"computing, memory, and evolution\", each of which directly addresses the pain points of current AI programming tools:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Persistent memory across sessions<\/strong>: The bottom layer uses SQLite FTS5 full-text search engine to maintain a persistent<code>MEMORY.md<\/code>Project files.<\/li>\n<li><strong>Multi-agent collaborative architecture<\/strong>: Through the three major modes of analysis and planning (Max Mode, sampling 5 solutions in parallel and selecting the best), development execution, and task orchestration, the main and deputy agents can work in parallel.<\/li>\n<li><strong>self-evolving system<\/strong>:<code>\/dream<\/code>The command automatically reviews historical sessions every week, removes duplicates and compresses them into long-term memory; the \"distillation\" function mines historical sessions for repetitive workflows that can be automated.<a href=\"https:\/\/chatgpt.com\" target=\"_blank\" rel=\"nofollow noopener\">ChatGPT<\/a> Dreaming and Anthropic<a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Dreaming has the same purpose but different approaches.<\/li>\n<li><strong>Voice programming<\/strong>: Based on Xiaomi\u2019s self-developed MiMo-ASR speech recognition technology, it supports voice command coding and architecture reconstruction, achieving true hands-free programming.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Benchmark performance<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">According to data released by Xiaomi\u2019s technology blog, the MiMo Code paired with the MiMo-V2.5-Pro \u200b\u200bmodel surpassed all three standard evaluations.<a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Code (with<a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Sonnet 4.6):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>SWE-bench Verified<\/strong>:82% (vs. <a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Code 79%)<\/li>\n<li><strong>SWE-bench Pro<\/strong>:62% (vs. 55%)<\/li>\n<li><strong>Terminal Bench 2<\/strong>:73% (vs. 69%)<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">What is even more noteworthy is that an internal test covering 576 developers, 474 real private warehouses, and 1,213 sets of A\/B comparisons showed:<strong>Within 200 steps, the two systems have a 50-50 win rate; after more than 200 steps, MiMo Code\u2019s winning rate rises to over 65%<\/strong>\u2014\u2014This is where the value of its persistent memory and state management architecture lies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It should be pointed out that these are all self-reported data by manufacturers.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">User experience\/limitations<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Advantages<\/strong>: One-click installation (one curl command for macOS\/Linux, npm for Windows), zero-configuration out-of-the-box, automatic import<a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Code's MCP server and custom skills.<a href=\"https:\/\/chat.deepseek.com\" target=\"_blank\" rel=\"nofollow noopener\">DeepSeek<\/a>,<a href=\"https:\/\/kimi.moonshot.cn\" target=\"_blank\" rel=\"nofollow noopener\">Kimi<\/a>, GLM, etc.).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>limitations<\/strong>: The V0.1.0 version number itself implies limited maturity; the \"limited time\" access to the free model means possible charges in the future, and the code context needs to go through Xiaomi servers; as a product of a Chinese technology enterprise, it may face the risk of compliance review by some organizations; the benchmark data has not been independently verified.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Overall Score<\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table>\n<thead><tr><th>\u7ef4\u5ea6<\/th><th>Score<\/th><th>evaluate<\/th><\/tr><\/thead>\n<tbody>\n<tr><td>functional completeness<\/td><td>8.0 \/ 10<\/td><td>The three major innovations of persistent memory + multi-agent + voice are outstanding, but the V0.1 feature set is still being expanded.<\/td><\/tr>\n<tr><td>\u6613\u7528\u6027<\/td><td>8.5 \/ 10<\/td><td>One-click installation, zero configuration, automatic import<a href=\"https:\/\/claude.ai\" target=\"_blank\" rel=\"nofollow noopener\">Claude<\/a> Code configuration; terminal native experience is smooth<\/td><\/tr>\n<tr><td>Cost-effectiveness<\/td><td>9.0 \/ 10<\/td><td>MIT open source + free model access + extremely low API pricing, 96% cache hit rate significantly reduces costs<\/td><\/tr>\n<tr><td>\u4e2d\u6587\u652f\u6301<\/td><td>7.5 \/ 10<\/td><td>Produced by the Xiaomi China team, Chinese can be understood naturally; documents and communities are mainly mixed in Chinese and English<\/td><\/tr>\n<tr><td>\u8f93\u51fa\u8d28\u91cf<\/td><td>8.0 \/ 10<\/td><td>The stability of long-term tasks is outstanding, and SWE-bench performs well; however, the benchmark is self-reported and has not been independently verified.<\/td><\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Overall rating: 8.2\/10<\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>\u5c0f\u7c73MiMo\u56e2\u961f\u4e8e6\u670810\u65e5\u6b63\u5f0f\u5f00\u6e90Mi [&hellip;]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[6],"tags":[],"class_list":["post-302","post","type-post","status-publish","format-standard","hentry","category-ai-coding"],"_links":{"self":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/posts\/302","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/comments?post=302"}],"version-history":[{"count":0,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/posts\/302\/revisions"}],"wp:attachment":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/media?parent=302"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/categories?post=302"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/tags?post=302"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}