--- title: "🛠️ Running Nintendo Games with 1GB Qwen Model Weights? nesformer Challenges the Limits of LLM Deterministic Computation: Open Source Daily" description: "Can a 1GB Qwen model weight actually run Nintendo games? This issue of \"Open Source Daily\" dissects nesformer, which garnered 287 points on Hacker News, to see how it compiles a 6502 CPU and game ROMs directly into a large language model. We will also introduce DeepSeek's official open-source development assistant that cuts task processing time in half, and an ambitious project aiming to open-source the entire commercial software ecosystem. Details coming up next." canonical_url: "https://blog.markkulab.net/en/open-source-weekly/open-source-weekly-2026-11-01" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2026-11-01T02:00:00.000Z" category: "Daily Open Source Goodies" tags: ["open-source", "podcast", "開源工具", "開源", "nesformer", "dsh-superagent-prototype", "everything", "Qwen", "DeepSeek", "Puter", "AI"] 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" --- # 🛠️ Running Nintendo Games with 1GB Qwen Model Weights? nesformer Challenges the Limits of LLM Deterministic Computation: Open Source Daily ## Introduction Can a 1GB Qwen model weight actually run Nintendo games? In this issue of "Open Source Daily", we dissect nesformer, which garnered 287 points on Hacker News, to see how it compiles a 6502 CPU and game ROMs directly into a large language model. We will also introduce DeepSeek's officially open-sourced development assistant that cuts task processing time in half, as well as an ambitious project aiming to open-source the entire commercial software ecosystem. More details coming right up. --- ## Today's Open Source Picks ### 1. nesformer: A proof-of-concept project compiling the Nintendo NES 6502 CPU into Qwen3.5 model weights - **What it is**: This is a proof-of-concept (PoC) project exploring the limits of Large Language Models (LLMs) as deterministic computers. Rather than a practical everyday emulator, it was built out of scientific and academic curiosity to answer whether LLM weights can precisely simulate complex hardware states. The project demonstrates to the tech community that, with a specialized state design, hardware instruction execution can be precisely simulated within LLM weights. - **Recent Buzz**: 287 points on Hacker News (148 comments), 254 GitHub stars, License: Other, Primary Language: Python. - **Key Features**: 1. Compiles the NES 6502 CPU, 2 KB of RAM, and game ROMs directly into the weights of a Qwen3.5-4B model, completely bypassing the need for any gradient descent training. 2. Utilizes DeltaNet's recurrent state as the machine's memory (RAM) to precisely predict CPU execution logs. 3. Provides a lightweight host program to handle the screen display (PPU), controller inputs, and interrupt signals, successfully passing the rigorous nestest test suite. - **Quick Start**: 1. Clone the project and install dependencies: ```bash git clone https://github.com/dbreunig/nesformer.git cd nesformer pip install -r requirements.txt ``` 2. Download the project-specific Qwen model weights from Hugging Face, and prepare a compatible game ROM in `.nes` format. 3. Run the emulation command in your terminal: ```bash python -m nesformer run roms/thwaite.nes --frames 600 --show ``` - **Comparison**: Unlike traditional NES emulators written in C/C++ (such as Nestopia), it does not rely on conventional code logic to simulate CPU registers and instruction sets. Instead, hardware instruction prediction and execution occur entirely within the weights of the Transformer model. - **Who it's for**: Tech enthusiasts who love diving into the underlying mechanisms of large models and want to understand the limits of LLMs acting as state machines. - **Link**: [https://github.com/dbreunig/nesformer](https://github.com/dbreunig/nesformer) --- ### 2. dsh-superagent-prototype: DeepSeek's officially open-sourced proactive development Agent prototype - **What it is**: This project addresses common pain points for R&D teams using AI assistants, such as high task latency, AI constantly interrupting team members, or token abuse. It provides a development Agent featuring task ticket isolation and subscription mechanisms, allowing the AI to write code, fix bugs, and submit PRs directly within an isolated environment. - **Recent Buzz**: 5,059 GitHub Stars (new project within 30 days), License: MIT, Primary Language: TypeScript. - **Key Features**: 1. Adopts a two-tier Router-Worker architecture, where the Router listens for GitHub or messaging app events, and the Worker executes specific development tasks and submits PRs in an isolated environment. 2. Supports team-customized rules with three modes (Off, Observe, and Auto) to prevent the Agent from abusing tokens. 3. Features a background task management mechanism that automatically moves shell commands to the background if they take longer than 5 seconds, ensuring the Worker can continuously receive new messages. - **Quick Start**: 1. Clone the project and install dependencies: ```bash git clone https://github.com/deepseek-ai/dsh-superagent-prototype.git cd dsh-superagent-prototype npm install ``` 2. Copy the environment configuration file and configure necessary keys such as `DEEP_SEEK_API_KEY` and GitHub App credentials: ```bash cp .env.example .env ``` 3. Once configured, you can directly prompt your AI assistant (such as Claude Code or Cursor) with: `Read SETUP.md in this repository and set up dsh-superagent with me.`, and let the AI guide you through the rest of the automated setup. - **Comparison**: Compared to single-session AI development assistants like Devin or Sweep, dsh-superagent utilizes task ticket isolation and subscription mechanisms. According to official test reports from the DeepSeek Harness team, this architecture slashes p95 task processing time from 29.5 minutes to just 15.7 minutes. - **Who it's for**: Software development teams looking to introduce AI collaborators to their GitHub projects and boost asynchronous development efficiency. - **Link**: [https://github.com/deepseek-ai/dsh-superagent-prototype](https://github.com/deepseek-ai/dsh-superagent-prototype) --- ### 3. everything: An MIT-licensed monorepo project reconstructing the commercial software ecosystem with open-source technology - **What it is**: This project addresses the pain point of wanting complete control over personal data and breaking free from subscription-based commercial software (like Office, Slack, and Photoshop). Initiated by the team behind Puter, the well-known WebOS project, it provides the self-hosting community with a comprehensive suite of web-based, AI-friendly open-source alternatives. - **Recent Buzz**: 6,178 GitHub Stars (new project within 30 days), License: MIT, Primary Language: JavaScript. - **Key Features**: 1. Managed as a monorepo, it currently includes over 50 open-source alternative applications spanning office, collaboration, creative, and developer tools. 2. All applications are primarily written in JavaScript/TypeScript, and most can run directly in the browser, making them extremely friendly for the self-hosting community. 3. Integrates the Repowise MCP server, allowing developers to connect the entire repository directly to AI code assistants like Claude Code and Cursor for deep analysis and customized modifications. - **Quick Start**: 1. Clone the entire project repository: ```bash git clone https://github.com/HeyPuter/everything.git cd everything ``` 2. Navigate to a specific application's directory (for example, the spreadsheet application `apps/spreadsheet`) and start it: ```bash cd apps/spreadsheet npm install npm run dev ``` - **Comparison**: Compared to single-purpose open-source alternatives (such as standalone LibreOffice or GIMP), everything provides a unified, web-based open-source software suite with native support for AI agent integration and invocation. - **Who it's for**: Engineers who enjoy self-hosting services, are looking for open-source alternatives to commercial software, or want to leverage AI to assist in web application development. - **Link**: [https://github.com/HeyPuter/everything](https://github.com/HeyPuter/everything) --- ## Wrap-up I've observed that whether it is extreme experiments treating LLMs as hardware emulators, or practical open-source frameworks launched by DeepSeek and the Puter team, the integration of AI and the open-source ecosystem is accelerating at an incredible pace. These projects are perfect for cloning and running yourself to experience the latest technological advancements. See you tomorrow! --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/open-source-weekly/open-source-weekly-2026-11-01) 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): Your website is live. Who checks its certificates, security settings and known vulnerabilities? A self-hosted Security Hub brings website scans and host monitoring together, deduplicates findings and compares scans after fixes. ### 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. 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