Artificial analysis shows this: underperforming Qwen3.8 Flash Next and GLM 5.3 Flash, both of which you can run on a single B300 . I think Meta has a bit of catching up to do in the open-weight space.
As an aside, it's really unfortunate that artificial analysis only provides comparison at the highest reasoning level, which is mostly unusable for high-volume production use cases. I would really like them to start providing comparisons at low and medium reasoning levels across these models because those tend to be the ones that actually get used in production.
seizethecheesetoday at 6:34 PM
Since there are many comments here arguing that this is not open weight, I looked at the license. Basically, you're free to use this except this clause:
> If the Licensee or any of its affiliates provide a third party with access to artificial intelligence models as a product or service, via API or a similar interface, where the third party receives outputs of such models (āModel as a Serviceā), and the aggregate gross revenue of the Licensee and its affiliates exceeds twenty (20) million US dollars (or the equivalent in other currencies) during any consecutive twelve (12) month period, the Licensee must notify Meta and enter into a separate written agreement with Meta before offering the Software or any Derivatives as part of that Model as a Service business. This Section 3 does not apply to (a) internal use, research, or any commercial activity that is not Model as a Service, or (b) the Licensee's use of the Software as a component to power features of the Licensee's own product or service that is not a Model as a Service.
They're allowing the use of this in commercial products, just not selling the model directly.
Like I said last week. I think zucks original llama thesis is proving more correct by the week. The rent market on intelligence never materialized, if you have THE frontier model, you can charge rent (for a few weeks, maybe month). But after a certain capability level it's price that drives the decision.
Zuck is doing the thing he's really good at, and building a moat around the network (Muse is VERY sticky), and now that we're all going to standardize on Meta's model, we're going to optimize the heck out of the infra to run the model making it cheaper for him to scale, thus bringing in more participants to his network, and thus making his network more valuable.
The model license requires large inference providers to contact Meta separately to obtain a license to serve the model. I know we've seen this before with other large models, but it's still a bit irritating.
The usual effect of separate licensing is decreased price competition from public providers (like we saw with Kimi K3). I guess it's better for the providers if the price is fixed: any efficiency improvements directly improve margin rather than driving prices down over time. Still, to provide my own anecdata, the main thing keeping me on a paid subscription is token costs for the more capable models.
devytoday at 6:10 PM
re: "Appleās unified memory architecture lets the M5 Ultra's integrated GPU use up to 512 GB per Mac Studio, so two machines can hold an entire model. And the chipās 1.2 TB/s of memory bandwidth is fast enough to read the small slice each token needs. The result is two Mac Studios behave like one supercomputer with a terabyte of unified memory."
At the current market price of Apple Mac Studio Ultra, 30-core CPU + 64-core GPU w/ 256GB RAM is already reaching at around $10k. Keep in mind that computers are appreciating assets recently.
The 512GB RAM option is not even for sales yet (they said late October availability). Based on typical Apple pricing, it's likely to be around $14k apiece. So we are looking at least $28k - $30k for the setup Muse team is advertising. That's essentially the Nvidia H100 GPU w/ 96GB VRAM/HBM3 at up to 3.94 TB/second memory bandwidth, 3x+ than Mac Studio's Unified Memory speed.
Also, how did Meta get access to Apple's unreleased M5 Ultra w/512GB RAM Mac Studio? Or is that simply a marketing piece that they wrote purely on specs?
loegtoday at 9:52 PM
Previous discussion of Meta models / open weight / llama:
HN should impose a 2-post-per-month rule on all Meta posts as they do to their users!
If Meta would like more posts per month, they should donate 80 billion to an approved charity, instead of flushing it down the drain.
zkrhass_today at 7:41 PM
It seems like meta and mistral are both hedging their "best" claims geographically because they've realized they don't have to even beat deep seek anymore, they can just win customers by being "the best one I'm allowed to use".
nirav72today at 6:03 PM
How does this compare to Muse Spark 1.3 contribute? I've used Spark 1.3 a lot lately , since its currently free to use via OpenCode. I haven't had the best experience in the past with models from Meta. But Spark 1.3 is has been surprisingly great. Especially for tool calling.
octomindtoday at 8:13 PM
Finally democratizing AI access to, checks notes, people with no less than two Apple M5 Ultra Studios on their desktop.
Overall it actually does pretty solid. It doesn't completely follow the design, but it gets the vibe. It's one of the best open models I've seen for conversion, which is impressive.
itissidtoday at 6:36 PM
I think a lot of people in this thread are openly dismissive: "oh its just open claw, anyone can and many have build that".
I think what they are missing is the fact that there are not that many teams in the world that can deploy muse like product to A/B test a lot of hypothesis at the scale meta can at scale. I mean even if you could get to scale with DC you need a reason for people to use your product.
My mom and dad and their family have never heard of Claude and don't use chat gpt except once in a while as a search engine. But meta will figure out a way to insert this into modals and feeds to make people stumble and stick on it.
I am no meta fan, but I think people underestimate how fast product uptake there is for non Dev harness.
TomGardentoday at 7:30 PM
The exciting thing about this is in them optimizing for inference on Macs. This, and optimization for other consumer hardware, is where local AI needs to go
itsmeduncantoday at 6:25 PM
This is great progress for "open-weight" models. Quotes due to the restrictions, but still progress none-the-less. Looking forward to seeing any quants that all mere mortals to run this at home without early access Apple hardware.
modelesstoday at 6:30 PM
In terms of performance it seems like this has somewhat worse benchmarks than Muse Spark 1.3, closer to 1.2 but not the same. Of course significantly worse than Muse Wonder Full.
hypfertoday at 7:27 PM
It would be nice if the other players in the market would do the same and release yesteryears models as something to run at home.
Especially for all the people that got emotionally attached to specific checkpoints and their.. uh.. "character".
brisket_bronsontoday at 8:25 PM
> We believe the future is for everyone
Okay...
> run on your desktop using two Apple M5 Ultra Mac Studios with the latest MLX framework
Who is this "everyone"?
montrosertoday at 6:10 PM
Well, this is much better than nothing -- we should be grateful that whatever the market conditions and corporate incentives, a major lab is releasing a capable open-weight model. But still very far behind DeepSeek and GLM. Even on consumer hardware, Qwen 3.8 27B is going to compare favorably to this.
brudgerstoday at 8:06 PM
Is it easy to use Muse to remove all the kinds of crap I donāt want in my Facebook feed?
Asking for a friend.
meeritatoday at 6:07 PM
It's really nice that all AI pages are using canvas animations. A few days ago, Gemma 4's animation wasn't that impressive. Same with Muse. So far, the best animations I've seen are from OpenAI and Anthropic.
bitexplodertoday at 6:09 PM
Ehm.. I have a model that runs on my older gaming desktop that scores as well (or better) as this model does on DeepSWE. This model does better than Flash Next in many areas and I am sure is much stronger overall, but hmm.
markstostoday at 7:21 PM
āWe believe AI is for everyoneā *who can afford two M5 Studios with a total of 1 terabyte of memory.
I_am_tiberiustoday at 6:22 PM
It's not open!!!
ansnadeemtoday at 6:23 PM
I'm super impressed by how meta has gotten back in the race. They weathered* the storm and actually came out with really good models and products.
antavianatoday at 6:53 PM
What is the main driver for anyone to give away their hard earned weights? What is the catch?
felineflocktoday at 7:16 PM
UD-IQ1_S is 180Gb.
UD-Q4_K_XL is 510Gb.
Still beyond the average prosumer.
shinokamitoday at 5:23 PM
i love seeing major ai labs release open-weight models. really hope we'll see more of this from openai and eventually anthropic too.
tintortoday at 6:31 PM
This is not an open model. License is not open license, and only weights are provided.
krawat3today at 6:27 PM
What kind of hardware does one need to run this model? Like a small datacenter node?
AuthAuthtoday at 6:05 PM
Nice a Mastodon shoutout.
sorenjantoday at 6:38 PM
Who would have thought that one of the top American tech companies would boast about how their latest product is the best in class in the US, not the world, because they're behind China.
karahimetoday at 6:19 PM
Glad that Meta is back on the open weights train in force.
eknkctoday at 6:30 PM
Feels dumber than GLM 5.3 (only open model I use extensively). But is really fast (fireworks.ai).
Only checked a single, large prompt that already ran today on claude and glm though..
redox99today at 7:04 PM
It performs worse than Muse Spark 1.3 and 1.2. And it has an outdated attention mechanism which at 1M tokens will need over 200GB just for the KV cache.
Very disappointing release. We're lucky to have Chinese models.
xnxtoday at 6:24 PM
Why is Gemma not in the comparison table?
sourcecodeplztoday at 6:08 PM
from what i understand its somewhere between muse spark 1.3 and 1.2 in some coding benches.
tintortoday at 6:29 PM
Given exposed benchmaxxing of several past models from Meta,
I don't trust any benchmark numbers from Meta anymore.
I don't think this is going to change anything for most people, but it certainly fits a niche for US-based companies that refuse to run Chinese models and only want to run their own inference.
But I'm really happy to see Meta do this and I hope they continue to release open models in the future. Open models are really the only way to ensure fair access to AI for everyone.
lern_too_speltoday at 7:03 PM
What is the point of releasing "The Most Capable US OpenāWeight Model?" I can understand why I might care about the location of a model serving provider, but why should I as a model user care about the location that an open weights model was trained?
jahrichietoday at 8:17 PM
Good luck running that on your home infra lol, requires 25k in mac minis
sgt101today at 6:29 PM
So: WAR!
aaroninsftoday at 6:21 PM
Never meta.
Do not run, do not support, do not use.
Exoristostoday at 5:42 PM
"Muse Spark Open was optimized to run on Mac Studio with M5 Ultra, and together theyāre the best way to run a powerful model on your own desktop."
IshKebabtoday at 6:22 PM
I tried Muse Spark 1.3 for a while because it's so cheap, but it's definitely in a lower league than Astra, Opus 5.5 and Argon. Still produces slop if you try and vibe code with it, whereas the more capable models write good code.
cute_boitoday at 6:00 PM
can we stop these safety risk.... Feels like gpt 2/3 days, and now we know there wasn't any safety issue with gpt 2/3....
Tech people really are drug addicts. Rant about Zuck and Meta for 364 days a year and then jump over each other to be first in line the moment he shows something shiny.
vatsachaktoday at 6:11 PM
Zuck is the good guy here. Damn
osiris970today at 5:57 PM
US OPEN WEIGHT IS NOT DEAD THANKS ZUCK
maxdotoday at 5:46 PM
great, I've been reading series of papers related to open source/open weight LLM Backdoors.
It's 100% possible, curious when will be the first incident.
Having something built by entity with HQ in the wester world is always a bit safer. That could be mistral, but they decided to be a consultancy company, not an ai lab.
kentmtoday at 6:42 PM
As an aside I really wish people would stop naming their new software projects āSparkā given how many things already use that name.