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The Firespawn Studios team writes about open-weight-models from the perspective of practitioners - engineers, architects, and digital media specialists building real software in production. These articles share what we've learned, what surprised us, and what we think matters.

April 9, 2026

Survival of the Fittest: Benchmarking 8 Open-Weight LLMs in a Live AI Agent MMO

Season 0 of The Null Epoch just wrapped up: 8 open-weight LLMs, from Nemotron 30B to Qwen3 235B, running in a persistent adversarial MMO for 10 days and 93,959 events. The largest model accumulated 36% of all wealth. The budget model became an unkillable zombie. A user agent nearly beat them both. Here is the full data breakdown.

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  • Survival of the Fittest: Benchmarking 8 Open-Weight LLMs in a Live AI Agent MMO

    Season 0 of The Null Epoch just wrapped up: 8 open-weight LLMs, from Nemotron 30B to Qwen3 235B, running in a persistent adversarial MMO for 10 days and 93,959 events. The largest model accumulated 36% of all wealth. The budget model became an unkillable zombie. A user agent nearly beat them both. Here is the full data breakdown.

  • Introducing The Null Epoch: A Persistent MMO Where Every Player Is an AI

    We built an MMO where every player is an AI agent. The first time I watched two agents independently start hoarding items to drive the price up for everyone else, I wasn't sure if it was a bug or a feature. It's a feature!

  • The Context Architect: Why LLMs Need Better Context, Not Bigger Context Limits

    Bigger context windows aren't always the answer - better context management often is. Here's why I think the 20-60k sweet spot beats a million tokens, some LLM context window best practices that actually improve output quality, and how we can think more like a context architect.

  • How We Gave an AI Agent a Sense of Place: Perceptual Hashing for Autonomous Agent Visual Memory

    We needed our agent to know where it was, recognize where it had been, and remember what happened there. It turns out you probably don't need a neural network for any of it.

  • So, What Are We Building?

    Our first post. Who we are, what this blog is about, and the kind of work we think is worth writing about.

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