@huang_chao4969: nanobot just built a Super Mario game for only $0.1 with a single prompt! One prompt → Full game. This is what token-ef…
Summary
nanobot v0.2.0 is released, featuring lightweight, token-efficient AI agents capable of long-horizon tasks. A demonstration shows building a Super Mario game with a single prompt for $0.1.
View Cached Full Text
Cached at: 05/19/26, 12:37 AM
nanobot just built a Super Mario game for only $0.1 with a single prompt!
One prompt → Full game. This is what token-efficient AI agents can do.
Just released nanobot v0.2.0 with /goal for sustained objectives, improved WebUI, and enhanced long-horizon capabilities!
Here’s the thing with long-running tasks - as they get more complex, everything becomes harder. Your memory gets bloated, tool usage becomes messy, and you’re dealing with hundreds of steps where just one screw-up ruins everything. Plus, nobody wants to burn through tons of tokens just to get unsatisfying results.
That’s why we’re building lightweight agents that are both affordable and reliable for long-horizon tasks.
official site: https://nanobot.wiki GitHub: https://github.com/HKUDS/nanobot
nanobot - Ultra-Lightweight Personal AI Agent
Source: https://nanobot.wiki/home
Ultra-LightweightPersonal AI Agent
Steady, Fast & Scalable · Light on Cost · Easy to Run
Install
pip install nanobot-ai
* Requires a Python environment.
Full install guide in README →
Agents that run anytime, anywhere — answers you can trust
nanobot
Hallmarks & Horizon
-
Lean Compact code,sensible context, andtoken budgets—predictable spend from day one.
-
Enduring Long-horizon: tens to hundreds of steps withsteady execution—context stays coherent.
-
Kernel Standardagent runtime kernel: embed inyour businessor daily life—one portable core.
MIT License
Contact
https://github.com/HKUDS/nanobothttps://x.com/nanobot_projecthttps://discord.gg/MnCvHqpUGBhttps://nanobot.wiki/cdn-cgi/l/email-protection#aed6dbccc7c0dccbc0cdddeec9c3cfc7c280cdc1c3
Similar Articles
Built a World Cup mini game with AI agents, not just prompt-to-code
A developer built a World Cup mini game using AI agents, showcasing an approach beyond simple prompt-to-code.
@FakeMaidenMaker: A lightweight personal AI agent that is small yet highly readable. Existing agent frameworks wrap the core loop in a black box; changing one detail means peeling through layers of abstraction, making even reading a chore, let alone secondary development. I'm recommending an ultra-lightweight open-source AI agent — nanobot. Designed for those who 'want to read and understand…'
Introducing the open-source ultra-lightweight AI agent nanobot. Its core loop is designed to be minimal and readable, making secondary development easy. It supports 10+ chat platforms including Telegram, Discord, Feishu, and multiple AI providers, with integrated long-term memory and MCP tool extensions.
@Saboo_Shubham_: The MATH here is INSANE for Multimodal AI agents. Nano Banana 2 Lite: ~3 cents an image, ~4 seconds each. Gemini Omni F…
The tweet highlights the remarkably low cost and fast speed of multimodal AI agents like Nano Banana 2 Lite (~3 cents/image, ~4 seconds) and Gemini Omni Flash ($0.10/sec video with native audio and editing), enabling affordable looping for agents.
@no_stp_on_snek: Ran this on Laguna S 2.1 in Poolside's own agent (pool), pointed at a local instance on a DGX Spark, using the prompt l…
A comparison of two AI coding agents building a Mario game: Laguna S 2.1 in Poolside's agent took 62 minutes with self-correction and passed tests, while a previous Qwen model took hours and needed human help; highlights oracle discipline and native harness advantages.
@gregpr07: /goal build GTA 6 Is this the AGI test? One prompt in -> full playable game out? How good can a single prompt get? http…
A tweet showcases a demo where a single prompt generates a playable open-city sandbox game reminiscent of GTA 6, hinting at AGI-level capability.