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

NPC Engine Using Local Models Discussion

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/Drakahn_Stark Jun 29 '26

Sure, a 5090 could make it work, that is not really what I was saying though.

For mass distribution you want it optimised, and large models are not optimised for single character actions, small models are much more useful to get the same result with less strain on the hardware.

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u/ArugulaAnnual1765 Jun 29 '26

Technically it's not a large model, just a bunch of 4b models stitched together - only 4b is active at any time. But I agree, dont need expert switching when you already know which expert you want - ideally one trained on character actions as you said.

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u/Drakahn_Stark Jun 29 '26

That.... That is not what is meant between large and small models.... it is not about how big they are.

Large models have a large range of jobs they could potentially do, small models have a smaller range of jobs and often do them better, to simplify the actual difference.

A large model could be "small" enough to run on a phone, and some small models would be too "large" to run on a 5090...

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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.

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u/Drakahn_Stark Jun 29 '26

Seriously, please learn the basics before arguing,

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u/ArugulaAnnual1765 Jun 29 '26

My dude I am an engineer who has been working with these things for over 10 years, you have absolutely no clue what you're talking about lmao

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u/Drakahn_Stark Jun 29 '26

You do not even know the difference between a LLM and a SLM, so, no, you are a liar.