Meta's Muse Code agent tackles 24-hour kernel optimization marathons
Muse Code and Muse Spark 1.2
Meta AI has released Muse Code (beta), a terminal coding agent powered by the new Muse Spark 1.2 model. Muse Code coordinates persistent subagents, uses a replay-exact event log for crash recovery, and ships with planning and stress-testing skills. Muse Spark 1.2, co-trained with Muse Code, shows gains in code generation, debugging, and long-horizon tasks. In a case study, the agent iteratively optimized GPU kernels over 1,000+ tool calls, achieving substantial speedups.
The agent continues to achieve substantial improvements over the provided baseline implementation.
- sams99
Unfortunately I find this too high risk, I entered my credit card, but can not set a limit. The best I can do is get an email alert. I feel like I am one oopsie away from getting a 100 dollar bill.
- tristanj
Meta is offering a 10x discount on input ($0.10 vs. $1.25/Mtok) and 20x discount on output ($0.20 vs. $4.25/Mtok) if you opt in to let them train on your data.
- WhitneyLand
They chose to compare against Open AI’s mid tier model Terra instead of Sol and still lost some benchmark against it.
They left Opus in and got beat in all but one benchmark.
Nothing wrong with trying to improve, but why the marketing games?
Instead of trying to say in the post you’re “closer” to frontier, first set a clear goal to beat the Chinese labs on price or performance and demonstrate it convincingly.
Then when your ready, come back and talk frontier without playing hide the model.
- bradfa
If you got the $20 in free credits from Meta for signing up when muse-spark-1.1 was release, please note that there's now small print stating "While using free credits your content may be used for product improvement" which was not present at muse-spark-1.1 launch when the credits were given out.
If you don't mind Meta retaining your data, the "Contributor" pricing is deepseek-v4-flash-level of low, roughly 1/10th normal muse-spark API pricing currently. Attractive if you're OK with them retaining and using your data.
- conradkay
https://pbs.twimg.com/media/HO-59jQaoAA_JZ1?format=jpg
Very interesting they have a way cheaper "contributor" version "used to improve our products", how much of that is price discrimination vs the data being that valuable?
Roughly DeepSeek V4 Flash pricing, though you can get V4 from providers that don't train on your data
- mchusma
This is a nice release and a solid improvement over Spark 1.1. It compares favorably with Grok 4.5. Not SOTA, but solid releases. I think they need to really get this more competitive with Deepseek V4 Flash / Luna pricing to move the needle.
- wiradikusuma
Hey guys I'm just wondering. Usually when someone announces a new model, they'll show you some fancy viz/video/images: "These are what my model can produce." I'm wondering if anyone is keeping track of these? Like in a gallery form, "Use this prompt to produce this output".
By itself is useful ("I want something like this, I'll just reuse the prompt and tweak"), but it can also be used as a "draw me a pelican on a bicyle" alternative. Basically feeding those prompts over model releases.
- andai
The most interesting thing here is the kernel optimization graph.
It look like all models were still improving, when they cut off the experiment.
It reminds me of a genetic algorithm. The graph is the same: long plateaus and then massive leaps.
The only difference between the models seems to be how quickly they arrive.