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Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

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Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#31

Post by IMTDb »

zoobab wrote: post #23
sparkling wrote: post #18

Earlier quoted context omitted.

Even if you had a 64GB machine: Are you willing to reserve 90% of your memory to run a LLM? With dirt cheap models like deepseek-v4-flash that will run "forever" on $10, the answer for me is clearly: no.

"With dirt cheap models like deepseek-v4-flash that will run "forever" on $10, the answer for me is clearly: no." When it's free, you are the product.

Deepseek flash is open weight, this means we can download and run that model without any connection to deepseek, no data/tokens/usage data ever reaches them. They cannot make us their product.

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#32

Post by lostmsu »

scrlk wrote: post #5

Will be interesting to see how Qwen3.8 27B compares against this once it releases this week. Seems like dense 30B is back in fashion? EDIT: An open weight version of Muse Spark 1.2 is going to be released as well: https://x.com/alexandr_wang/status/2086756152034066792 https://xcancel.com/alexandr_wang/status/2086756152034066792

It seems worse than 3.6, but a bit smaller.

UPD. was wrong on smaller, it's actually much larger

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#33

Post by prplxd_nihilist »

zoobab wrote: post #23
sparkling wrote: post #18

Earlier quoted context omitted.

Even if you had a 64GB machine: Are you willing to reserve 90% of your memory to run a LLM? With dirt cheap models like deepseek-v4-flash that will run "forever" on $10, the answer for me is clearly: no.

"With dirt cheap models like deepseek-v4-flash that will run "forever" on $10, the answer for me is clearly: no." When it's free, you are the product.

I see many people saying deepseek and other chinese providers have always been profitable. Also they show their training costs publicly. Can't say for sure since I have not used it personally, but I think they'll for sure outlive the western SOTAs.

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#34

Post by Gecko4072 »

scrlk wrote: post #5

Will be interesting to see how Qwen3.8 27B compares against this once it releases this week. Seems like dense 30B is back in fashion? EDIT: An open weight version of Muse Spark 1.2 is going to be released as well: https://x.com/alexandr_wang/status/2086756152034066792 https://xcancel.com/alexandr_wang/status/2086756152034066792

Makes me feel hopeful. Things felt more positive around the llama 3 era. Now it’s like a dark, dreadful race.

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#35

Post by halJordan »

sparkling wrote: post #18
sajithdilshan wrote: post #10

Still needs 32-64GB memory to run it locally. 64GB Macbook pro with an M5 chip costs more than 4k Euros in Germany. A more practical model would be a language specific (e.g Python or JVM language) and excellent at tool calling and reasoning. Maybe that way they can shrink it even more.

Even if you had a 64GB machine: Are you willing to reserve 90% of your memory to run a LLM? With dirt cheap models like deepseek-v4-flash that will run "forever" on $10, the answer for me is clearly: no.

It's the size of a big vm. There's nothing wrong with reserving that much working space for one item.

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#36

Post by mettamage »

mihaelm wrote: post #26
sajithdilshan wrote: post #10

Still needs 32-64GB memory to run it locally. 64GB Macbook pro with an M5 chip costs more than 4k Euros in Germany. A more practical model would be a language specific (e.g Python or JVM language) and excellent at tool calling and reasoning. Maybe that way they can shrink it even more.

I'm sooo happy I pulled the trigger on upgrading and getting a new laptop (with 64 GB RAM) last summer. Feels like it was just in time before the exponential price jumps.

Bought an M1 64 GB for 2000 euro’s second hand a year ago. That was sweet

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#37

Post by idiotsecant »

ishtanbul wrote: post #29
mihaelm wrote: post #26

Earlier quoted context omitted.

I'm sooo happy I pulled the trigger on upgrading and getting a new laptop (with 64 GB RAM) last summer. Feels like it was just in time before the exponential price jumps.

Pulled the trigger?

Common phrase.

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#38

Post by cmrdporcupine »

Havoc wrote: post #13

The favourable comparisons to Gemma 4 and qwen3.6 look promising!

Those two offer MoE variants, this doesn't seem to.

Dense model makes it dog slow on anything without HBM. Max 15tok/sec on decode on DDR5 systems like a Spark or a Strix Halo -- and that's at 4 bit quant.

Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

#39

Post by karimf »

sajithdilshan wrote: post #10

Still needs 32-64GB memory to run it locally. 64GB Macbook pro with an M5 chip costs more than 4k Euros in Germany. A more practical model would be a language specific (e.g Python or JVM language) and excellent at tool calling and reasoning. Maybe that way they can shrink it even more.

Practically ~20GB with KV cache

> We quantize weights to ~4-bit, bringing the LM under 20 GB. We validated minimal to no degradation on agentic tasks under compression.

https://www.reddit.com/r/LocalLLaMA/comments/1vkgsum/introdu...

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