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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

#321

Post by michelsedgh »

Aurornis wrote: post #311
throwup238 wrote: post #276

Earlier quoted context omitted.

> It's common, if not inevitable, for people who feel strongly about $topic to conclude that the system (or the community, or the mods, etc.) are biased against their side. One is far more likely to notice whatever data points that one dislikes because they go against one's view and overweight those relative to others. This is probably the single most reliable phenomenon on this site. Keep in mind that the people wit…

> The problem is that when there are any sides, they spend the top 100 comments rehashing the same arguments, often over a political bugbear or web design faux pas. This is a problem with any upvote/downvote based site, in my experience. It only takes a couple people who are highly engaged and who have a lot of free time to refresh the comment section and downvote everyone who disagrees with them. Some times I’ll wri…

the downvoting rings ( or bots ) are very active here. I think they're mostly bots, but who knows i guess

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

#322

Post by younglunaman »

avaer wrote: post #101

I lament the comments saying this in any way redeems Meta (the company). The researchers releasing this stuff have almost nothing to do with Meta other than being bankrolled by the slaughterhouse. You aren't the customer, you are the pawn in big tech's game of thrones. Your good will is a commodity to be traded, almost literally. It will be used against you the moment it's convenient. This is open weights because Met…

Crazy idea, maybe people can be happy a new open model got released, and still have nuanced ideas on meta as a whole.

A company is a big thing there's a lot of moving pieces, why do we have to evaluate it as a whole instead of just seeing it as it is?

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

#323

Post by xscott »

wolttam wrote: post #261
xscott wrote: post #236

Earlier quoted context omitted.

I've got nothing but hand-waving, but after you've extracted all the smarts from every piece of text ever created, how do you get more? Alpha Go had a game where the models could compete against each other. That let it become super human. What's the intelligence game we can create for LLMs? Even if you invent something, will it make the model smarter in a way the market values enough? Then there's a race to use the w…

I think you’re thinking about it in slightly the wrong way. We’re not throwing more data at frontier models in hopes they get more/better capabilities somehow. We’re either: setting up a verifiable task, and doing RLVR to get the model better at achieving that task. Or we’re simply asking: “What do we want the model to do that it can’t now, and how do we curate data that would benefit it on that task?” Most useful ca…

Yeah, there's room for improvement at every level, but your specific example: How do you get more and more difficult tasks where you can steer the training? To me, that seems limited by how creative humans can be. How do you get past AGI and into ASI with that? If the AIs make the tasks, how could we encourage them to be useful? Maybe you could push for harder and harder math proofs, but other than that I'm not sure.

Anyways, I'd be thrilled to see exponential (or faster) growth. Bring on the Culture, Accelerando, whatever. I just don't see it yet.

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

#326

Post by rapind »

ericmay wrote: post #171
avaer wrote: post #101

I lament the comments saying this in any way redeems Meta (the company). The researchers releasing this stuff have almost nothing to do with Meta other than being bankrolled by the slaughterhouse. You aren't the customer, you are the pawn in big tech's game of thrones. Your good will is a commodity to be traded, almost literally. It will be used against you the moment it's convenient. This is open weights because Met…

It’s rather amusing to me to read comments like this, and then simultaneously whenever a Chinese company or team releases open-weight models or whatever there is a giant round of applause, America is so behind, and there’s nothing but positive things to say about the intelligent, creative, and well-intentioned Chinese engineers (which is true, America certainly doesn’t have a monopoly on great people). Don’t you know…

> When an American company does anything? Doom. And. Gloom. The engineers? Taken to the slaughterhouse! America? Behind! The public? Bamboozeled!

I think I've always had a pretty healthy amount of cynicism towards China. In recent years my cynicism towards the US has increased significantly. I don't see all of my US peers with cynicism, but I think you're living in an age of grift, corporate capture, and unheard of corruption. I also think there's nuance to both. There are some US and Chinese companies and people that I do respect regardless of what's going on politically. (Meta / Zuck isn't one of them though...)

I live in the 51st state though, so maybe I'm just overreacting...

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

#327

Post by andy99 »

The gguf is up and works, I don’t know if it’s them or unsloth that’s facilitated this but it’s nice because e.g. Inkling still doesn’t appear to have support in llama.cpp which makes it irrelevant to a class of user.

Unfortunately I don’t have enough experience with Qwen 27B to immediately compare, but I do it’s Qwen 3.6 35B A3. It’s much slower obviously but it seems to be way more efficient with its thinking to the point that using it might actually be faster. I find Qwen and some others rehash the same things over and over when thinking without getting anywhere, in mg limited checks here Muse is much better.

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

#328

Post by [deleted] »

Manfrednotfunny wrote: post #27
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.

I'm waiting for the speed/quality per dollar metric to go down a little bit further and then I will def run it at home. Its not just that you send a sentence to an API endpoint, you always send EVERYTHING to that agent as a context. You want to analyse your spending history? You now send everything to someone. Either no one cares but understands this implication on how easy it is to really capture you or no one reall…

[deleted]

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

#330

Post by NegativeLatency »

xscott wrote: post #132
cube00 wrote: post #123

Earlier quoted context omitted.

Considering how all the big players are playing fast [1] and loose [2] with limits, billing [3] and adding undisclosed changes that burn your tokens on autopilot [4], it can't happen soon enough. [1]: Limits may change without notice, including due to capacity constraints. - https://support.google.com/gemini/answer/16275805?sjid=14713... . [2]: "standard limits" are never defined - https://support.google.com/gemini/a…

Not to mention all the other ways they can screw you: - Middle of the day, servers busy? Swap to Sonnet while pretending it's still Opus. Many people won't notice, and nobody can prove anything if they suspect. - Middle of the night, server load is light? Put it into extra thinky mode so it burns more tokens to ramp up the bills. Flip the switch where it gets really pedantic about writing lots of extra test cases and…

I find Claude doing a lot of pointless confirmation at night when it will ask me about things that it would normally just do during the day.

Frustrating to be like “do X overnight, don’t ask me for input” and come down to find it having worked for a few minutes and then stopped.

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