--- title: "🧪 1.3B Runs on Laptops: MiniCPM-OCR-1.0 Turns Local Invoices into JSON in Seconds: Local AI Lab" description: "Hugging Face recently released MiniCPM-OCR-1.0, a 1.3B parameter model that lets laptops read complex invoices and PDFs locally in seconds. In this episode, we will also introduce Sage-A1.5, a 35B MoE agent model that runs on a single RTX 4090. How does it help you automatically break down engineering requirements and self-correct code? We'll tell you shortly! These two open-source powerhouses, featuring local deployment, free access, and Apache 2.0 licensing, are absolute must-haves for engineers." canonical_url: "https://blog.markkulab.net/en/local-ai-lab/local-ai-lab-2026-10-28" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2026-10-28T02:00:00.000Z" category: "On-Premise AI Lab" tags: ["local-ai", "podcast", "地端模型", "lora", "開源模型", "MiniCPM-OCR-1.0", "Sage-A1.5", "OCR", "AIAgent", "MoE"] language: "en" license: "CC BY 4.0" license_url: "https://creativecommons.org/licenses/by/4.0/" attribution: "when reusing or quoting, credit the author and link back to the original" --- # 🧪 1.3B Runs on Laptops: MiniCPM-OCR-1.0 Turns Local Invoices into JSON in Seconds: Local AI Lab A new 1.3B parameter model, MiniCPM-OCR-1.0, recently landed on Hugging Face, enabling laptops to parse complex invoices and PDFs locally in seconds. In this issue, we will also introduce Sage-A1.5, a 35B MoE agent model that can run on a single RTX 4090. How does it help you automatically break down engineering requirements and self-correct code? We will tell you in a moment! These two open-source powerhouses, which are local-first, free, and licensed under Apache 2.0, are absolute must-haves for engineers. --- ## Featured This Issue ### 1. openbmb/MiniCPM-OCR-1.0: Ultra-lightweight 1.3B Document Parsing and OCR Model, a Powerful Tool for Local Invoice and PDF Structuring - **What is it**: Released by OpenBMB, MiniCPM-OCR-1.0 is an ultra-lightweight vision-language model with only 1.3B parameters, specializing in document parsing and OCR tasks. It uses the developer-friendly Apache 2.0 open-source license, making it highly suitable for commercial applications. It is particularly adept at handling Traditional and Simplified Chinese and English documents, complex tables, and charts. - **Use Cases**: - **Scenario 1: Privacy-secure automated invoice and receipt processing**. When software engineers need to develop a completely offline financial system, they can simply input images of invoices or receipts. By leveraging the model's Key Information Extraction (KIE) capabilities, they can extract the store name, transaction date, and amount directly via prompts, outputting clean JSON. - **Scenario 2: PDF document parsing pipeline for local RAG systems**. When you need to build a Retrieval-Augmented Generation (RAG) system for your company and face thousands of scanned PDFs containing complex tables, mathematical formulas, and charts, you can use this model to quickly convert them into structured Markdown text, solving the formatting issues of traditional OCR. - **Scenario 3: Digitization of old or mobile-captured documents**. For digital archivists or researchers dealing with skewed, blurry, or low-light mobile photos of ancient texts and historical documents, this model can accurately restore text and paragraph order, digitizing them along with chart contents. - **Hardware Requirements**: According to the official model card, the model has only 1.3B parameters and comes in various quantized versions such as GGUF, GPTQ, and AWQ. Developers can easily run the GGUF version directly on standard laptops or workstations. Additionally, the official release includes the DSpark speculative decoding acceleration scheme, which the documentation notes can boost end-to-end processing efficiency by about 55%, making it highly friendly for local environments with limited hardware resources. - **Current Traction**: It currently has a trending score of 111 on Hugging Face, with 791 downloads and 184 likes, making it a rising star to watch. - **Comparison**: According to OpenBMB's official tests, MiniCPM-OCR-1.0 achieves a throughput of approximately 1.2 pages per second. It leads in multiple document parsing benchmarks, such as OmniDocBench, with the official team claiming its throughput is about 1.49 times that of PaddleOCR-VL-1.6 and 3.62 times that of MinerU2.5 Pro. - **How to Get It**: The official README indicates that you can directly load the GGUF version via `llama.cpp` to run a local OpenAI-compatible server using the command: `llama serve -hf openbmb/MiniCPM-OCR-1.0-gguf:Q4_K_M`; or deploy it using vLLM with the command: `vllm serve openbmb/MiniCPM-OCR-1.0`. - **Link**: [Hugging Face Page](https://huggingface.co/openbmb/MiniCPM-OCR-1.0) --- ### 2. InternScience/Sage-A1.5: A 35B MoE Advanced AI Agent Model That Runs on a Single RTX 4090, Specializing in Complex Task Decomposition - **What is it**: Sage-A1.5 is a 35B Mixture-of-Experts (MoE) agentic model open-sourced by the Shanghai Artificial Intelligence Laboratory. Built on Qwen3.6 and licensed under Apache 2.0, it is specifically optimized for long-horizon task execution, tool calling, and agent orchestration. - **Use Cases**: - **Scenario 1: Autonomous Coding Agent**. When software engineers develop automated code-generation tools, they need a model that can decompose complex system requirements into multiple sub-steps, automatically call external tools (such as a Code Interpreter or search engine) for testing, and even inspect error logs to self-verify and correct code when execution fails. - **Scenario 2: Local enterprise R&D and regulatory intelligence analysis**. R&D personnel within enterprises need to analyze competitor intelligence or complex regulations. By leveraging the model's agentic orchestration capabilities, they can dispatch tasks to multiple parallel sub-agents to gather data and compile a comprehensive analysis report, keeping all confidential data completely local. - **Scenario 3: Exploratory research on scientific datasets**. When dealing with large, complex scientific datasets, researchers need a model that can perform multi-step data analysis planning and dynamically adjust its next-step analysis strategy based on intermediate charts and data, achieving highly autonomous exploration. - **Hardware Requirements**: According to the official technical report and model card, although Sage-A1.5 is a 35B MoE model, only about 3B parameters are activated per token. In BF16 precision, the weight size is around 65.4 GiB, which drops to about 19.6 GiB after 4-bit quantization (Q4_K_M). Third-party evaluations indicate that under Q4_K_M quantization, the model, combined with an 8K token context length, can fit entirely within a single RTX 4090 (24 GB VRAM), bringing powerful agent capabilities to personal workstations. - **Current Traction**: Highly popular on Hugging Face, it currently has a trending score of 299, with 8.2k downloads and 350 likes. - **Comparison**: The technical report from the Shanghai Artificial Intelligence Laboratory indicates that compared to its predecessor, Agents-A1, Sage-A1.5 shows significant improvements in engineering and agentic tasks. For instance, it scored 17.6 points higher on SWE-bench Pro and 14.0 points higher on SWE-bench Multilingual. In the BrowseComp benchmark, Sage-A1.5 achieved a score of 81.7%, surpassing the previous generation's 75.5%. - **How to Get It**: The official README indicates that using the SGLang framework is recommended for high-performance deployment. The startup command is: `python -m sglang.launch_server --model-path InternScience/Sage-A1.5 --port 8000 --mem-fraction-static 0.8 --context-length 262144 --reasoning-parser qwen3 --tool-call-parser qwen3_coder`. - **Link**: [Hugging Face Page](https://huggingface.co/InternScience/Sage-A1.5) --- ## Summary As we can see from this issue's selection, the open-source community is rapidly evolving toward two extremes: extreme lightweighting and powerful agentic capabilities. Whether you want to handle document structuring on your laptop with MiniCPM-OCR-1.0 or build automated agents on your workstation with Sage-A1.5, local hardware can now handle it with ease. Go ahead and pick one to download and try on your machine. See you in the next issue! --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/local-ai-lab/local-ai-lab-2026-10-28) License: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — when reusing or quoting, credit the author and link back to the original ### About the author **[Mark Ku](https://blog.markkulab.net/en/author/mark-ku)** — Software engineer - 10+ years as a software engineer - Built North-American e-commerce and AI SaaS subscription billing ### Free tools built by the author All of these are free to use: - [Free PDF Sign Tool](https://blog.markkulab.net/en/tools/pdf-sign): Online PDF sign tool — draw, type, or upload a signature, then drag, resize, and download. Everything runs in your browser; nothing is uploaded. - [VS Code Refactory](https://blog.markkulab.net/en/tools/refactory): Refactory is a VS Code refactoring extension: 34 actions plus a 37-rule code-smell inspection layer with a Code Health dashboard, across 18 languages, backed by 534 tests. It learns your repo's conventions: where interfaces live, where DI is registered, whether 'use client' belongs. It ranks files by git churn × complexity so you know what to fix first, and hands any smell to the Claude Code already on your machine. Free to use, and your source never leaves your computer. - [DB-Kit Database Manager](https://blog.markkulab.net/en/tools/db-kit): DB-Kit is a lightweight, cross-platform database manager built with Tauri + Rust + React. Manage MySQL, MariaDB, PostgreSQL, SQL Server, Oracle, SQLite, MongoDB, Redis, Kafka, Elasticsearch and RabbitMQ from one consistent interface: passwords encrypted in the OS keychain, SSH tunnels, full CRUD, a visual query builder, stacked multi-statement result sets, cross-connection data transfer, schema & data compare with sync SQL and schema snapshots, Excel / CSV import & export, visualized execution plans, ER diagrams, scheduled backups, SQL stress testing with p50–p99 latency percentiles, a 15-rule SQL review engine, Review & Run (AI review plus per-statement backups and an auto-generated rollback script), Kafka message browsing with monitoring & alerts, an SSH terminal with SFTP / FTP, Docker / Kubernetes, remote desktop (RDP / VNC / RustDesk), file / folder compare, stored procedure integration tests, six UI languages, a built-in AI assistant (a local CLI or any Anthropic / OpenAI-compatible API; natural-language SQL, AI review and tuning advice) and the dbk CLI. Free and open source (MIT), with installers for Windows, macOS and Linux. - [VS Code Super Mermaid](https://blog.markkulab.net/en/tools/super-mermaid): Super Mermaid is a VS Code extension for beautiful Mermaid diagrams out of the box: auto-colored live preview, mouse pan & zoom, high-res PNG / SVG export, 21 templates and multiple themes. Free and open source (MIT). - [React Super Mermaid](https://blog.markkulab.net/en/tools/react-super-mermaid): react-super-mermaid is an open-source React component library: render beautiful Mermaid diagrams with a single , with built-in colorful / sketch themes, pan & zoom, in-diagram search, and high-res SVG / PNG export. Lightweight, SSR-safe, fully typed. Free and open source (MIT). - [Jira / Confluence Super Mermaid](https://blog.markkulab.net/en/tools/jira-super-mermaid): An Atlassian Forge app: write Mermaid syntax directly inside a Jira issue or a Confluence page and get flowcharts, sequence diagrams, state machines and Gantt charts. 11 diagram types, SVG / PNG export, light and dark themes, full CJK support. Runs on Atlassian: your diagrams live in your own site and the app calls no third-party service. Free, coming soon to the Atlassian Marketplace. - [Mermaid Live Preview](https://blog.markkulab.net/en/tools/mermaid-preview): Write Mermaid in your browser, see it render instantly, and share the whole diagram as a single link. No sign-up, nothing uploaded to a server, and mermaid.live share links work as-is. - [React Intl Phone Number](https://blog.markkulab.net/en/tools/react-intl-phone-number): react-intl-phone-number is an open-source React component: framework-agnostic and antd-free, with E.164 in/out, a searchable flag / country-code dropdown, configurable validation levels (strict / mobile-strict / loose), themeable CSS, and i18n — phone logic powered by google-libphonenumber. Lightweight and fully typed. Free and open source (MIT). - [Uptime Kuma Cluster](https://blog.markkulab.net/en/tools/uptime-kuma-cluster): Turn single-node Uptime Kuma into a highly available cluster: OpenResty + Lua smart load balancing, shared MariaDB state, health checks and automatic failover, plus cluster-management REST APIs. One Docker Compose command to start. Free and open source (MIT). - [AI Podcast Cut](https://blog.markkulab.net/en/tools/ai-podcast-cut): Drop in a recording and it removes fillers and stutters, levels loudness segment by segment, and sends a second agent to review every cut. Cut points snap to word boundaries and zero crossings, every splice gets a fade, and sentence-end breaths are preserved. Desktop app for Windows, macOS and Linux. MIT licensed; the Windows installer bundles ffmpeg. - [AI Video Cut](https://blog.markkulab.net/en/tools/ai-video-cut): Pick something in your video: type it (face, license plate, phone screen, logo), click points or drag a box, or let Claude Code / Codex pick it. AI Video Cut tracks it frame by frame, then mosaics or blurs it, recolors it, pins stickers and text to it, swaps a screen or poster for your own image or video, or removes it using background that other frames actually captured. Plus sequence editing, local captions and an AI assistant. Free, open-source (MIT) Windows desktop app (macOS / Linux experimental) that runs locally, nothing uploaded. - [open-pos restaurant POS](https://blog.markkulab.net/en/tools/open-pos): One computer and one receipt printer is enough to open the shop. Your data lives on your own disk, no subscription, no lock-in, MIT licensed. Money is integer New Taiwan dollars with tax split by the statutory formula, so sales + tax always equals the total. Printing goes straight over ESC/POS on TCP 9100, with no vendor driver. Tauri + Rust + SQLite desktop app, v1.0 in development. - [.NET e-commerce API template](https://blog.markkulab.net/en/tools/dotnet-ecommerce-api): An e-commerce backend API template built on .NET 10: Controller → Service → Repository layering, Autofac convention-based registration, SqlSugar for MySQL / MariaDB and SQL Server, Redis cache and message queue, Hangfire jobs, JWT auth, and an extensible payment provider module (ECPay, Newebpay). Apache 2.0. - [Open Token Monitor team AI usage](https://blog.markkulab.net/en/tools/open-token-monitor): Collect token usage and equivalent cost from every employee's AI coding tools into a hub you host yourself: PostgreSQL, org roster, dashboards compared by company and department, and a reports API. Electron and Rust/Tauri clients upload every 30 minutes. MIT licensed, one Docker command. - [ai-security-monitor defensive security](https://blog.markkulab.net/en/tools/ai-security-monitor): ai-security-monitor is a single Rust binary for your computers and servers. It finds unusual connections, rates them safe / unknown / suspicious / dangerous against 26 public threat-intel sources, and checks firewalls, open ports, vulnerabilities and 60 hardening rules. Security Hub shows the whole fleet, and Claude Code / Codex explain it in plain words. MIT, free, self-hosted. ### Daily podcasts - [Mark's Tech Insights — Daily AI News](https://blog.markkulab.net/en/category/tech-news): Daily curated AI and tech trends. Catch the latest developments via audio summaries — covering AI applications, software architecture, DevOps, and engineering practice. — RSS: https://blog.markkulab.net/feed.xml - [AI股市蝦聊](https://blog.markkulab.net/en/category/ai-stock-chat): Every trading day, an AI-analyzed take on the Taiwan stock market, delivered as a two-host conversation covering the session and the next-day outlook. — RSS: https://blog.markkulab.net/ai-stock-chat/feed.xml - [開源好物日報](https://blog.markkulab.net/en/category/open-source-weekly): A daily two-host pick of free open-source tools surfaced from real Hacker News, GitHub, and Reddit buzz — what pain they solve and the fastest way to get started. — RSS: https://blog.markkulab.net/open-source-weekly/feed.xml - [AI 運動日報](https://blog.markkulab.net/en/category/sports-weekly): Two hosts talk NBA, MLB and world sport every day — scores, records and the stories behind them, from a Taiwanese fan perspective. — RSS: https://blog.markkulab.net/sports-weekly/feed.xml - [AI 國際新聞快報](https://blog.markkulab.net/en/category/world-news): A daily two-host briefing that makes sense of the past 24 hours in world news — geopolitics, the global economy, conflict and security, disasters and climate — from a Taiwanese perspective, neutral and fully sourced. — RSS: https://blog.markkulab.net/world-news/feed.xml - [地端 AI 實驗室](https://blog.markkulab.net/en/category/local-ai-lab): Every day, a two-host look at open-weight models and LoRAs you can actually run on your own machine: what they are for, whether your GPU can handle them, and how they compare — sourced from official model cards. — RSS: https://blog.markkulab.net/local-ai-lab/feed.xml - [AI 行銷日報](https://blog.markkulab.net/en/category/ai-marketing): Every day, two hosts break down the latest in AI for marketing, advertising, SEO/GEO and content marketing: practical, never sponsored, every story sourced. — RSS: https://blog.markkulab.net/ai-marketing/feed.xml - [AI 資安日報](https://blog.markkulab.net/en/category/ai-security): Every day, two hosts cover the latest where AI meets cybersecurity: LLM and AI agent vulnerabilities, prompt injection, model supply-chain risks and AI-powered attacks, from a defense-first angle with every story sourced. — RSS: https://blog.markkulab.net/ai-security/feed.xml ### Newsletter [Subscribe to the newsletter](https://blog.markkulab.net/en/subscribe) — Be the first to know about new posts. No spam, unsubscribe anytime.