Can I run this on my RTX 5090?
Yes they have quants for 32GB and 20GB use-cases (including mmproj and kv cache + context)
Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
151–160 of 682 posts
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#152Will 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.
Qwen thinking is really good in Mandarin; and probably natively trained the most there.
Try a system prompt requiring it to think in Mandarin, while still delivering the response in the user’s language.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#153I 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…
what makes Meta so bad ???? they just your average billion dollar company
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#154Earlier quoted context omitted.
How is 30B smaller than 27B?
They say it is trained with quantization awareness, so it should only be 15GB or so. Qwen was only trained in FP8 with QAT. UPD, NVM, got misled by comments here. It is actually almost 60 GB so much larger
Quantization awareness doesn’t change the size of the weights, just means it won’t degrade when quantized. QAT = quantization aware training. They will both be very similar in size at the same quant.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#155I 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…
How is this non-sequitor the top comment?
Certain topics bring out the hidden Reddit inside.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#156Earlier 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…
These kind of tricks will completely break API customers and be super visible, since most companies deploying API at scale have ample telemetry, evals, etc.
Although, selectively applying it to consumer subs is probably beyond likely at this point.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#157I 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…
I'd also argue this is the case for any company releasing open weights. They're not righteous, they're marketing. That's not necessarily a bad thing! They're releasing some great stuff for free and we benefit from that. Every company doing this has a motivation to not release these for free.
Alibaba, Google, Moonshot, Thinking Machines, etc are not releasing their models for free because they love to. They want to grab market share. I'll take it.
I still will not use a hosted Meta product, but damn this model looks solid.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#158I 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…
Meta and its products, as a whole, is a threat to your kids, your mental health, your community's health and the planet as a whole. It is just sad and very repulsive everyone fell so easily addicted to their social drug. Yes - it is a drug, and it is hard to get off from. Nothing redeems them at this point of time, they are doing exactly ZERO to redeem. Tossing open weight models (not opensource!!) is not a basis for…
Social media, often owned and perpetuated by Meta, has poisoned the world. It is not redeemable at this point.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#159Earlier quoted context omitted.
Well if you're spending thousands on API tokens already, you could just drop the same amount on a 128GB MacBook Pro and that's a one time cost.
If you're dropping thousands on API tokens, you're going to be slowed down at least 10x trying to do everything on a single MBP.
But you could grab a 5090, and paired with some DRAM for MoE offloading of bigger models, and be a happy camper with 1.8TB/s of memory bandwidth.
Or just use Luna honestly. Worth considering if you’re ok with hosted APIs.
Re: Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
#160Earlier 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…
Ugh... didn't think about extra thinky mode in the middle of the night.
So many ways for enshittification here.