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

research.meta.ai

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

#561

Post by lukeschlather »

aqme28 wrote: post #250
gdhkgdhkvff wrote: post #217

Earlier quoted context omitted.

Why do you say API based llms looking iffy at best? Do you just mean current profitability due to market pressures from some companies’ subsidized investor money? Surely, even if you’re just using open weights models, it should theoretically be cheaper to use them in a highly optimized cloud architecture(even with vendor markups) rather than each person serving their own models from much less efficient (and more impo…

LLMs are becoming commoditized, which means the margins are trending to zero. It's a lot less exciting to spend another trillion on a new model if you can barely make any profit. Meta getting out of the game might be the smarter move.

Companies are going pretty quiet about costs, but I see no reason to believe the cost to train a model exceeds $5B. Moonshot AI's entire funding is like $5B, their $300M revenue is negligible but not nothing. Renting the compute to train a model like Kimi K3 cannot possibly exceed $5B and is probably under $1B. It's probably at least $100M, but also plausibly not. I don't think it's likely Meta would be giving away models for free if the compute cost to train them was in the billions. This 30B parameter is tiny, that's not billions of dollars, that's likely millions, maybe even less.

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

#562

Post by andy99 »

dofm wrote: post #555
bitexploder wrote: post #549

Earlier quoted context omitted.

I have a custom A3B proxy that caps its thinking off. It is a known issue with the model that Qwen themselves documented but is almost never addressed in any harnesses. I also patched up a few other known bugs in the proxy. I highly recommend you shim A3B and when it hits 2K thinking tokens inject (paraphrasing) 'Time to wrap it up bud! Get to work' into its thinking stream. It almost always gets to work. If it needs…

Fascinating, thank you. I am trying to switch to pi from opencode (my own thinking loops and burnout are a challenge lately). It had not occurred to me that you could nudge it to stop thinking with a proxy. Nice idea. Will favourite your comment and come back to it. ETA: Incidentally you've helped me put into words the difference between the way Muse Glimmer thinks to the way Qwen thinks. There is a clear sense of ur…

Having spent a good part of the day with it, glimmer reminds me of Rorschach from The Watchmen. No unessential parts of speech, action oriented, brief and to the point. From a token perspective anyway it’s great, and it seems to hold its own well against more verbose models.

I really do feel like it’s effective tok / s is way higher because it doesn’t waste them.

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

#563

Post by barcoder »

mmaunder wrote: post #249

Remember when we needed 200 servers for an enterprise website because Apache used one process or thread per connection - and Nginx collapsed that into a single box overnight? That moment for LLMs is near. It’s going to move us from the big iron era of AI to small portable brains. Nature has already proved it’s possible with 20 watts and very little heat generation. And I think the data center buildout will end in car…

It'll need a change in architecture for that to happen. For example Geometric Reasoning that's being actively worked on by people like this:

https://www.sophontic.ai

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

#564

Post by alexeiz »

dofm wrote: post #527
ignitioncar wrote: post #523

[flagged]

I haven't really got that far in, but it writes in a sort of clipped, geeky note form in the reasoning traces without too obvious claudeisms, it seems to have been trained to have a level of wit, almost. Like, in the car wash test, this was in the thinking traces: “Walking won't get the car washed.” and: “Perhaps answer: Walk if you want to wash yourself? No” Which made me laugh out loud. Even in the final answer: -…

I got Muse Glimmer to say "Drive the car, walk yourself." The logic is unbeatable.

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

#565

Post by dofm »

andy99 wrote: post #562
dofm wrote: post #555

Earlier quoted context omitted.

Fascinating, thank you. I am trying to switch to pi from opencode (my own thinking loops and burnout are a challenge lately). It had not occurred to me that you could nudge it to stop thinking with a proxy. Nice idea. Will favourite your comment and come back to it. ETA: Incidentally you've helped me put into words the difference between the way Muse Glimmer thinks to the way Qwen thinks. There is a clear sense of ur…

Having spent a good part of the day with it, glimmer reminds me of Rorschach from The Watchmen. No unessential parts of speech, action oriented, brief and to the point. From a token perspective anyway it’s great, and it seems to hold its own well against more verbose models. I really do feel like it’s effective tok / s is way higher because it doesn’t waste them.

I am very struck by the way open weights LLMs seem to reflect a culture.

I don't really enjoy the way Qwen writes prose, and I find its thinking a bit exhausting, though it clearly writes very good code.

I like the neutral, clear way the Gemma models write, which I sometimes use to get myself a "getting started" document on something I want to understand; it also summarises well. It is neutral, sensible, un-showy. It writes in a way that is fairly close to what I would use for documentation. The 12B and 26B models are also very good for talking about art and photography. Analysing my own photographic work has helped me more than I expected it to.

This model, honestly, has made me smile. It also feels like it is more creative at a given temperature than Gemma. I am trying to motivate myself to do something quite open-ended so I asked it about what other people's considerations might be in my situation, and at the risk of anthropomorphising, the things it has come up with feel like the work of a more curious mind, somehow. More eclectic. I have enjoyed testing it and I really want to test it more, which might help me get over a motivation hump there, too.

(I am also exploring its hard-wired policies by asking it to analyse some studio art nude work I have done; it definitely thinks out loud about its policies in a way I have not seen Gemma do.)

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

#566

Post by [deleted] »

notnullorvoid wrote: post #487
uncivilized wrote: post #480

Earlier quoted context omitted.

I’m sure you could find this exact same comment regarding technology in 1999.

You can find it today for gaming. Even despite the outlandish rise in hardware costs, there is very little demand for cloud gaming.

[deleted]

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

#567

Post by bitexploder »

dofm wrote: post #555
bitexploder wrote: post #549

Earlier quoted context omitted.

I have a custom A3B proxy that caps its thinking off. It is a known issue with the model that Qwen themselves documented but is almost never addressed in any harnesses. I also patched up a few other known bugs in the proxy. I highly recommend you shim A3B and when it hits 2K thinking tokens inject (paraphrasing) 'Time to wrap it up bud! Get to work' into its thinking stream. It almost always gets to work. If it needs…

Fascinating, thank you. I am trying to switch to pi from opencode (my own thinking loops and burnout are a challenge lately). It had not occurred to me that you could nudge it to stop thinking with a proxy. Nice idea. Will favourite your comment and come back to it. ETA: Incidentally you've helped me put into words the difference between the way Muse Glimmer thinks to the way Qwen thinks. There is a clear sense of ur…

You really have to get the models to end their thinking. Almost any commercial model serving has safe guards like this to tune how much they think.

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

#568

Post by cyanydeez »

BoredomIsFun wrote: post #463
kolbe wrote: post #241

Earlier quoted context omitted.

Qwen3.6 27B is the go-to medium sized model for coding, so beating it is not a small achievement

There is a finetune Qwen3.6-27B-Fable-Fus-711-UnHeretic-NM-DAU-NEO-MAX-NEO which seems to be as good at coding as vanilla Qwen, but way, way better at creative writing than Qwen and even better than Gemma 4 26 and 31b.

Yeah, this became my main coding model.

It seems to know tooling and coding.

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

#569

Post by michelsedgh »

PaulHoule wrote: post #395
Aurornis wrote: post #358

Earlier quoted context omitted.

I don't think they're bots and I don't even think they're organized. In my experience with other communities, it only takes 3-5 people with a lot of free time to crush conversations they don't like. On a fast moving comment section a wrongthink comment can be buried into the bottom half of the comments with only a few early downvotes.

When I used to run a spam factory my impression was that success on Reddit was all about avoiding the downvote brigades that would nuke you before you got your first 5 upvotes. Write a post on proggit where you confess that you are partially in it for the money or have any interest in the business of software and hoo boy, that's why I migrated to HN.

I still think bots run the /new and what gets to the first page shrugs

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

#570

Post by cyanydeez »

wronglebowski wrote: post #8
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’s really interesting timing, Qwen over thinking is what kills it for me. I’m just glad we have more options in this size class now.

Llamscpp provides reasoning budget and message. You can use the message to redirect it.

Once you get the agent and message consistent,itll keep moving.

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