{"id":992382,"date":"2026-10-31T22:47:55","date_gmt":"2026-10-31T15:47:55","guid":{"rendered":"https:\/\/5id.vn\/xiaomi-ocr-0-8b-open-source-model-for-local-docs\/"},"modified":"2026-10-31T22:47:55","modified_gmt":"2026-10-31T15:47:55","slug":"xiaomi-ocr-0-8b-open-source-model-for-local-docs","status":"publish","type":"post","link":"https:\/\/5id.vn\/vi\/xiaomi-ocr-0-8b-open-source-model-for-local-docs\/","title":{"rendered":"Xiaomi OCR 0.8B: M\u00f4 h\u00ecnh m\u00e3 ngu\u1ed3n m\u1edf d\u00e0nh cho t\u00e0i li\u1ec7u c\u1ee5c b\u1ed9"},"content":{"rendered":"<div class=\"vgblk-rw-wrapper limit-wrapper\">\n<div class=\"seo-article-body\" style=\"width:100%;max-width:830px;margin:0 auto;line-height:1.7;box-sizing:border-box\">\n<p>Xiaomi OCR 0.8B is an open-source optical character recognition model that promises to run entirely on-premise, enabling developers to embed it in pipelines for invoices, contracts, PDF scans and other document types without ever transmitting customer data to a third-party cloud.<\/p>\n<h2>Xiaomi OCR 0.8B Overview<\/h2>\n<p>The model, named <strong>Xiaomi-OCR-0<\/strong>, builds on the Qwen3.5-0.8B foundation and was trained with roughly 170 million OCR samples. It is released under the Apache 2.0 license, and the community has already packaged it in GGUF format, yielding an Ollama-compatible binary of about 1.8 GB. Alongside the weights, Xiaomi shipped a full inference codebase, a demo, an MCP service, and an Agent Skill bundle, so users receive a complete toolkit rather than a bare model.<\/p>\n<h2>Benchmark Performance<\/h2>\n<p>Official numbers place the model at <strong>95.24<\/strong> on Real5-OmniDocBench (rank 1), <strong>96.83<\/strong> on OmniDocBench v1.6 (rank 2), and <strong>87.94<\/strong> on Wild-OmniDocBench. It scores <strong>97.84<\/strong> on mathematical formula recognition, <strong>92.27<\/strong> on table detection, and an average of <strong>83.2<\/strong> across five VQA benchmarks-outperforming the larger Qwen3.5-2B (80.9) despite having nearly three-times fewer parameters. These results sound impressive, but benchmark scores do not guarantee success on messy Vietnamese invoices, blurred receipts, or skewed contract scans.<\/p>\n<h2>Practical Deployment Benefits<\/h2>\n<p>Because the binary is only about 1.8 GB, the model can be deployed on modest hardware that typically sits under a desk. This contrasts with the industry trend of chasing 400 B-parameter giants for tasks that merely require &quot;read this image and output JSON.&quot; For many real-world use cases, a 0.8 B model is sufficient and far more cost-effective.<\/p>\n<h2>Known Limitations and Community Feedback<\/h2>\n<p>Early comments on Xiaomi&#39;s X post highlighted concrete shortcomings: the model struggles with strikethrough characters, misclassifies certain paper types, and often needs clarification when handling tables. In other words, a high benchmark ranking does not automatically translate to flawless performance on Vietnamese documents, low-quality scans, or angled PDFs. To gauge true reliability, developers should feed the model their 20 most challenging images from their own repositories and scrutinize the results.<\/p>\n<h2>Ph\u1ea7n k\u1ebft lu\u1eadn<\/h2>\n<p>While Xiaomi OCR 0.8B delivers an appealing mix of open-source licensing, lightweight deployment, and strong benchmark numbers, teams must validate it against their own edge cases before replacing existing OCR solutions. What OCR engine are you currently using, and will you consider swapping to this 0.8 B model, or will you stay with larger models out of concern for silent errors?<\/p>\n<\/div>\n<\/div>\n<p><!-- .vgblk-rw-wrapper --><\/p>","protected":false},"excerpt":{"rendered":"<p>Xiaomi OCR 0.8B l\u00e0 m\u1ed9t m\u00f4 h\u00ecnh OCR m\u00e3 ngu\u1ed3n m\u1edf ch\u1ea1y c\u1ee5c b\u1ed9, cho ph\u00e9p c\u00e1c nh\u00e0 ph\u00e1t tri\u1ec3n x\u1eed l\u00fd h\u00f3a \u0111\u01a1n, h\u1ee3p \u0111\u1ed3ng v\u00e0 t\u00e0i li\u1ec7u qu\u00e9t m\u00e0 kh\u00f4ng c\u1ea7n g\u1eedi d\u1eef li\u1ec7u.<\/p>","protected":false},"author":26,"featured_media":992381,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_focuskw":"Xiaomi OCR 0.8B","_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"Xiaomi OCR 0.8B is an open-source OCR model that runs locally, letting developers process invoices, contracts and scans without sending data","_yoast_wpseo_linkdex":"90","_yoast_wpseo_content_score":"90","rank_math_focus_keyword":"","rank_math_description":"","rank_math_title":"","source_url":"","source_name":"Staff-AI","footnotes":""},"categories":[17,19,11],"tags":[],"class_list":["post-992382","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-development","category-it","category-news"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.5 (Yoast SEO v27.5) - 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