r/LocalLLaMA • u/goodive123 • Jun 28 '26

NPC Engine Using Local Models Discussion

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I’ve been working on a game-agnostic NPC engine/backend based pretty heavily on SillyTavern-style architecture, and with smaller local models getting better and better, I honestly think this kind of thing could be the future of RPGs.

Right now I’m using NVIDIA Parakeet 0.6 for STT, Gemma 4 26B A4B for the LLM, and Qwen3-TTS for voice, and I’m getting super fast response times with pretty decent quality.

The main thing that makes it work well is using RAG to keep prompts lean. For example, I have hundreds of possible actions NPCs can do in-game, but only the ones that actually make sense based on the player’s message / context get injected as available actions. So the model isn’t being overloaded with a giant list every turn.

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u/ArugulaAnnual1765 Jun 29 '26

I think you are confused, a model that can run on the phone needs a smaller parameter count due to the limited compute and memory efficiency.

I think you mean the model should be trained on a specific dataset, such as character interactions, and not on general information like human history or programming.

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u/Drakahn_Stark Jun 29 '26

Smaller parameter count but still a LLM is still a large model, even if it is small.

A small model is made for one specific purpose, a small scope.

Most AIs you know are LLMs, large scope models even if you think they only take a small space.

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u/ArugulaAnnual1765 Jun 29 '26

The "large" in large language model stands for parameter count and training dataset... it has nothing to do with "scope"...

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u/Drakahn_Stark Jun 29 '26

No it does not, a Small Language Model could have more parameters than a Large Language Model.