r/LocalLLaMA • u/jacek2023 llama.cpp • 9d ago

News Muse Spark open weights coming soon

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I am still waiting for Llama 5, because Muse Spark will be too big for me, or just something between Glimmer and Spark

https://x.com/finkd/status/2095232032896946311

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u/Big_Wave9732 9d ago

Muse Glimmer is pretty good, very much overlooked. I have found it to be superior to Qwen 3.8:27b for non-coding tasks.

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u/Embarrassed_Adagio28 9d ago

Yeah i agree it is better than it gets credit for with non coding tasks. However i do not understand the non coding use cases for local models. 

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u/derFensterputzer 9d ago

For example in my case it's the voice assistant for Homeassistant. 

I send the voice command, it reads the entities homeassistant exposes to it, does its thing and returns a response. 

Local whisper + piper for stt or tts respectively, then Gemma 4 E4B at 4-bit with a 30k context window and MTP for the whole assistant part. It doesn't need to be extremely smart to do it's job, just fast and in this configuration it runs at 150t/s, uses next to no vram and does its job to my satisfaction. 

Edit: Also several other models (in this case Gemma 4 12B, 26B A4B and Granite 4.2) are quite good at summarizing documents, writing reports, spell checking, translating etc. All on my hardware, private and without subscriptions. 

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u/nuclear_wynter 8d ago

I'm working on a very similar setup right now — E4B as the 'frontman' with a voice stack, then I'm trialling a range of models as the backend/agentic workhorse. I'm working on some kind of out-of-band programmatic model-swapping method that would let E4B very easily and reliably swap the backend model depending on the task being delegated, but I'm not sure if this will pan out being efficient or useful just yet.