The article analyzes the recent AI API price war, detailing DeepSeek’s step‑by‑step token‑price reductions, Xiaomi’s 99% cut that aligns its MiMo‑V2.5 Pro tier with DeepSeek, the underlying technical optimizations that enable lower costs, and the broader market shift toward cost‑driven competition.
The article details how Xiaomi's Vision Forge AI engine creates a high‑fidelity, lively 3D pet avatar from a single photo, integrates it into the SU7 cockpit with precise matting and motion, and explains the underlying model architecture, reinforcement‑learning enhancements, and inference optimizations that make the feature both realistic and responsive.
Xiaomi unveiled the MiMo‑V2.5 and MiMo‑V2.5‑Pro large language models, highlighting up to 50% lower API cost, multimodal perception, token‑efficiency gains, benchmark superiority over Claude Opus 4.6 and GPT‑5.4, and real‑world demos that built a full compiler in 4.3 hours and a video‑editing web app in 11.5 hours.
This article analyzes the recent release of OpenAI's GPT‑5.4 mini and nano, MiniMax's self‑evolving M2.7, and Xiaomi's MiMo‑V2 family, detailing their architectures, benchmark scores, pricing, target scenarios, and the broader industry shift toward lightweight, fast, and autonomous AI agents.
Xiaomi’s newly unveiled MiMo‑V2‑Pro, codenamed Hunter Alpha, is a trillion‑parameter LLM with a 1 million‑token context window that tops OpenRouter usage, achieves the second‑best domestic and eighth‑best global scores on Artificial Analysis, and delivers strong benchmark results across PinchBench, ClawEval, and SWE‑bench.
After a week of anonymous dominance on OpenRouter, Xiaomi revealed that the top‑ranking Hunter Alpha and Healer Alpha models are its MiMo‑V2‑Pro and MiMo‑V2‑Omni, respectively, and introduced the MiMo‑V2‑TTS voice model, detailing their massive parameters, benchmark scores, pricing, multimodal capabilities, and a clever blind‑test launch strategy.
Xiaomi Miclaw, an AI agent built on the MiMo large model, launches a limited closed beta to demonstrate system‑level tool access, multi‑turn context management, IoT ecosystem integration, and self‑evolution capabilities while emphasizing data security and user‑controlled permissions.
CVPR 2026 accepted 14 Xiaomi papers spanning long‑video understanding, multimodal reasoning, GUI agents, and autonomous driving, each accompanied by arXiv and GitHub links, and introducing novel frameworks such as REVISOR, EMO‑R3, TimeViper, MSJoE, SafeGRPO, GUI‑CEval, ProactiveMobile, ParkGaussian, UFO, TraqPoint, SimScale, MeanFuser and DVGT.
The International Conference on Learning Representations (ICLR) 2026 accepted multiple Xiaomi papers covering multimodal reasoning, reinforcement learning, GUI agents, autonomous driving, audio generation and benchmark design, each presenting novel frameworks, data‑centric training tricks and strong experimental results that advance the state of the art.
Xiaomi’s washing‑machine project, evaluated by the China Light Industry Federation, showcases three core innovations—independent drum suspension, a high‑integration water system, and an AI‑driven full‑frequency drive—that together deliver low‑noise, high‑cleanliness performance and are deemed internationally leading.
Xiaomi’s MiMo‑V2‑Flash, a 309B‑parameter MoE LLM with only 15B active weights, uses Hybrid SWA, Multi‑Token Prediction and Multi‑Teacher On‑Policy Distillation to cut KV‑cache by six times, boost inference speed 2.6×, and achieve performance comparable to DeepSeek‑V3.2, Kimi‑K2 and near‑GPT‑5 High, including a 73.4% SWE‑Bench code‑agent score.
The article explains Xiaomi's "Hotspot Compilation Acceleration" in Surge OS 3, detailing how the compiler identifies high‑frequency code paths, partitions hot and cold sections, and iteratively optimizes binaries, resulting in a 4% CPU load reduction and a 10% efficiency gain for smoother mobile experiences.
AAAI 2026 accepted seven Xiaomi research papers—two oral presentations—covering multimodal sound editing, embodied 3D agent scheduling, scalable Text-to-SQL schema linking, parallel speculative decoding, long‑form speech QA, high‑level spatial navigation, and VLM‑driven autonomous‑driving adversaries, each with concrete datasets, methods, and benchmark gains.
This week’s tech roundup covers OpenAI’s GPT‑5‑Codex launch, Google and OpenAI’s gold‑level ICPC performance, Apple’s iOS 26 release, TCL’s world‑first SQD‑Mini LED TV, Suzhou’s AI‑city summit, Alibaba’s DeepResearch open‑source, OpenAI’s bubble outlook, Huawei’s open‑source strategy, Xiaomi’s 17 series and audio model, and Ant Group’s AI‑glasses framework.
The article provides a comprehensive technical analysis of Xiaomi’s newly launched Xuanjie O1 mobile SoC, covering its 3nm N3E process, ten‑core CPU layout, Arm Immortalis‑G925 GPU, 6‑core NPU, memory and storage features, benchmark results, and detailed comparisons with Snapdragon, MediaTek and Apple flagship chips.
The article examines Xiaomi’s open‑source ha_xiaomi_home integration for Home Assistant, detailing its technical requirements, supported protocols, and code structure, while analyzing how developers can learn IoT standards, contribute to the project, and entrepreneurs can create compatible products, value‑added services, and foster ecosystem growth in China and beyond.
This article introduces Xiaomi’s open‑source Home Assistant integration, explains its benefits over third‑party solutions, and provides step‑by‑step instructions—including git commands—to install, update, and securely configure the component for managing Xiaomi IoT devices within Home Assistant.
Xiaomi Vela, an open‑source IoT operating system built on the NuttX kernel, now powers over 47 million devices, offering high‑performance real‑time capabilities, rich components, multi‑protocol connectivity, and developer tools, while Xiaomi expands its ecosystem through GitHub, Gitee, and B‑station.
Xiaomi Vela, an open‑source IoT operating system built on the NuttX kernel, offers high‑performance real‑time capabilities, rich components, unified frameworks, and extensive connectivity, and has been deployed on over 47 million devices, with source code now publicly released under Apache 2.0.
This article presents Xiaomi's work on LLM‑based Agent technology, covering its perception‑thinking‑action pipeline, technical framework, prompt management, executor and API platform, workflow, optimization strategies, evaluation metrics, and future directions for AI assistants.
This article details Xiaomi’s practical deployment of Trino, covering its architectural role, core and extended capabilities, performance comparisons, integration with Iceberg and Spark, operational enhancements, multi‑cluster and ad‑hoc query scenarios, future cloud‑storage plans, and a Q&A session.
This article presents Xiaomi's comprehensive metric system framework, covering its definition, business pain points, the OSM and MECE methodologies, model design principles, data warehouse construction, metric management, and future outlook, illustrating how a unified data platform drives efficient business decision‑making.
This article details Xiaomi's three‑year journey of adopting Apache Doris across dozens of internal services, describing the transition from a Spark‑SQL‑based Lambda architecture to a unified MPP database, performance benchmarks, data ingestion pipelines, compaction tuning, two‑phase commit, single‑replica writes, monitoring, and community contributions.
Xiaomi introduced the full‑size humanoid robot CyberOne, detailing its human‑service design, lightweight actuators, advanced perception sensors, AI‑driven interaction capabilities, and the broader challenges and strategic motivations behind developing such sophisticated robots in the current tech ecosystem.
This talk presents the end‑to‑end deployment of Kyuubi as a unified, high‑availability SQL gateway on Xiaomi’s big‑data platform, covering its integration, architecture upgrades, multi‑engine support, performance gains, operational improvements, and future roadmap.
This article details Xiaomi's end‑to‑end metadata platform, covering its three‑layer architecture, the evolution of full‑domain metadata, real‑time lineage, precise measurement, and how these capabilities enable data map, governance, cost control, and quality improvements for future business empowerment.
The author recounts how a high‑school love for graphic design led to Windows Mobile theme hacking, a prize‑winning custom Wubi input layout, Xiaomi theme creation with MAML DSL and WebSocket push, and a later product concept that was ultimately blocked, illustrating the evolution from UI hobbyist to self‑taught developer.
The article examines how Chinese tech founders Lei Jun, Luo Yonghao and Jia Yueting idolized Steve Jobs, adopted his marketing, software‑first, and “reality‑distortion” tactics, achieved early breakthroughs, then faced dramatic setbacks, illustrating broader shifts in China’s product‑management landscape.
The article presents an in‑depth overview of Xiaomi's knowledge graph, describing its evolution, core technologies such as entity linking, knowledge fusion and concept mining, and illustrating how it powers diverse AI‑driven services like smart Q&A, virtual assistants, e‑commerce and financial applications.
The article details Xiaomi's unified streaming data platform, its three‑generation evolution from Scribe/Kafka/Storm to Talos and Flink, the current architecture supporting billions of records daily, and future plans to unify offline and real‑time warehousing with Flink SQL.
The article presents a comprehensive overview of Xiaomi's streaming platform, detailing its three‑stage evolution from a Scribe‑Kafka‑Storm stack to a Flink‑driven real‑time data warehouse, describing its architecture, components, challenges, migration strategies, job and SQL management, and future roadmap.
This article explains how Xiaomi leveraged NFC technology to create a versatile digital door card, outlines the rapid visual redesign process undertaken in 2019, and shares the design concepts that blend Xiaomi's brand identity with youthful, tech‑forward aesthetics.
This article summarizes Ouyang Chen's GDevOps 2016 talk, covering the definition of DevOps, four personal viewpoints, Microsoft's three‑phase transformation, Xiaomi's rapid release pipeline, key principles, metrics such as time‑to‑detect, and essential tools for building an efficient DevOps culture.
The article details Xiaomi's evolution of internet‑finance risk control—from early limit and frequency rules that cut bad‑debt by a third, through adopting the Drools rules engine for rapid deployment and gray‑release, to leveraging random‑forest machine‑learning models and extensive user profiling that reduced fraud by roughly 40%, while addressing privacy and operational challenges.
