LLM-powered NPCs running on your hardware
Hey HN, My team is open-sourcing the inference stack and fined-tuned models we use to create LLM-powered NPCs: https://github.com/GigaxGames/gigax The generative agents paper [1] pioneered the idea of prompting LLMs to create autonomous NPCs. But existing implementations require multiple calls to an LLM to make the agent plan its day, chat with people, and interact with its environment [2]. Our approach allows NPCs to be stepped at runtime with a single pass on consumer-grade hardware, with reasonable latency. To achieve this, we've fine-tuned open-source LLMs [3] to…
In plain words
Gigax Games has open-sourced an inference stack and fine-tuned language models for creating NPCs that run on consumer hardware. The system enables autonomous non-player characters to plan their day, interact with environments, and chat with players using a single inference pass rather than multiple API calls. Developers can deploy these LLM-powered agents with reasonable latency by using custom function-calling formats optimized for speed, making it practical for game development without requiring high-end server infrastructure.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN, My team is open-sourcing the inference stack and fined-tuned models we use to create LLM-powered NPCs: https://github.com/GigaxGames/gigax The generative agents paper [1] pioneered the idea of prompting LLMs to create autonomous NPCs. But existing implementations require multiple calls to an LLM to make the agent plan its day, chat with people, and interact with its environment [2]. Our approach allows NPCs to be stepped at runtime with a single pass on consumer-grade hardware, with reasonable latency. To achieve this, we've fine-tuned open-source LLMs [3] to parse a text description of a 3d scene, and respond with custom actions like `greet <someone>`, `grab <item>`, or `say <utterance>`. This simple whitespace-separated « function calling » format is less verbose than json and thus helps with inference speed. We're also using the Outlines library [4] to force the model to adhere to this format. We're launching an API and we're looking for partnerships with studios to integrate our tech into upcoming games. Would love to connect if this is of any interest to you! Thanks in advance for your feedback :) [1] https://arxiv.org/abs/2304.03442 [2] https://github.com/joonspk-research/generative_agents/tree/m... [3] https://huggingface.co/Gigax (phi-3 fine-tune) [4] https://github.com/outlines-dev/outlines/tree/main
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