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Published on 28.01.2026
TLDR: Moltbot, the viral open-source AI agent formerly known as Clawdbot, faces a common problem: running proactive AI agents gets expensive fast. Kilo Gateway solves this by offering exclusive free models and cost-effective pricing on frontier models.
Summary:
The AI agent space just got a lot more interesting. Moltbot has become one of the fastest-growing open-source projects, accumulating over 50,000 GitHub stars in just 48 hours and reportedly driving significant Mac Mini sales. Creator Peter Steinberger has been navigating quite a journey - handling explosive growth while dealing with a trademark-related name change from Clawdbot to Moltbot after a request from Anthropic, fending off bad actors trying to hijack his handle, and coordinating a Product Hunt launch with Kilo.
But here's the uncomfortable truth that nobody talks about enough: running AI agents is expensive. Unlike reactive AI tools where you pay per query, proactive agents like Moltbot are constantly working in the background - monitoring websites, checking news sources, scanning emails and calendars, running scheduled tasks, and executing multi-step workflows. All that consumption adds up fast when you're paying standard API rates. Users report spending significantly more than expected within their first weeks.
The local inference route isn't practical for most people either. Running the latest open-weight models like GLM 4.7 locally at 4-bit quantization requires at least 40GB of GPU VRAM (that's a $4000+ investment) and 200GB of RAM (another $1000+). For the average developer, that's just not realistic.
Kilo Gateway is positioning itself as the solution by offering a mix of free and cost-effective models. They're providing exclusive free access to models like GLM-4.7 and MiniMax M2.1 - which work great for many agent tasks - while also giving pay-as-you-go access to frontier models like Claude Opus 4.5 and GPT-5.2 without markup when you need more complex reasoning capabilities.
For architects and teams considering AI agents in their workflows, this highlights an important consideration: the economics of always-on AI agents are fundamentally different from occasional API calls. You need to think about model tiering strategies - using cheaper or free models for routine monitoring and background tasks, reserving expensive frontier models only for complex reasoning that actually requires them. Kilo Gateway's approach of mixing free models with pay-as-you-go premium access is a pattern worth considering when designing agent architectures.
Key takeaways:
Tradeoffs:
Link: How Kilo Gateway Supercharges Moltbot (Previously Clawdbot)