Daniel Gross announces a $100,000 challenge to make Meta's Muse Spark Open run faster, starting with GPU kernels and then SGLang serving
We're launching a $100,000 challenge to see who can make Muse Spark run fastest:
Context
A paid contest aimed at inference speed signals where open model builders want help: serving large models faster and cheaper, rather than only training better ones.
Muse Spark Open is the open weights version of Meta's Muse Spark, and SGLang is an open source engine for serving large models. The challenge asks outside engineers to beat SGLang's current speed on this model.
Deep dive
On October 22, Daniel Gross posted that a $100,000 challenge was launching to see who can make Muse Spark run fastest, with a link to the contest site. This is an announcement of a contest, not a model release. The post does not say who funds the prizes, and the contest page, read after the post, lists Meta, Paradigm and Andromeda in its sign in example.
According to the challenge page, the contest has two stages. The kernel stage runs from October 22 at 11 AM Pacific to November 4 at 11:59 PM Pacific. Entrants write a GPU kernel, which is tested on random inputs against a reference implementation and timed against SGLang on one H200, using the same inputs and a CUDA graph. The score is how much faster the entry is than SGLang. The page lists five kernel problems, including attention decode, a mixture of experts layer and full decode and prefill layers.
The serving stage runs from November 5 at noon Pacific to November 19 at 11:59 PM Pacific. Entrants submit a diff to SGLang that serves the model on a full eight H200 node, using hidden multi turn coding conversations at 1, 4, 16 and 32 concurrent users. The page says the top kernel competitors get priority for node time, and only the serving stage winners receive prize money.
The listed prizes are $50,000 and a signed H200 for first place, $30,000 for second, $10,000 for third, $3,000 for fourth, $2,000 for fifth and $1,000 each for sixth to tenth. The page says top contestants may be offered an interview for a role at Meta. When read, its leaderboard already showed a best entry at about 1.45 times SGLang's speed.
What to expect next
Watch the leaderboard as the kernel stage runs through November 4, and whether the best kernels hold up on the hidden serving workload in the second stage. Whether the winning changes are merged into SGLang or released openly is not stated on the page. Entrants and observers have also raised questions about GPU access and whether the benchmark can be gamed, and organizers have not published a response in the sources reviewed here.