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[ARTICLE · art-92264] src=dotnetperls.com ↗ pub= topic=large-language-models verified=true sentiment=↑ positive

Muse Spark in OpenCode

Meta Superintelligence Labs' Muse Spark 1.1, a close-to-frontier LLM, successfully fixed a Rust program bug in two prompts via OpenCode and OpenRouter, costing 33 cents. The model's changes were correct and it communicated tersely, ending with 'No match or if' rather than verbose explanations.

read1 min views1 publishedAug 11, 2026

I tested Muse Spark 1.1, a new close-to-frontier LLM from Meta Superintelligence Labs, on my Rust program. Given that I have used small local models to maintain my Rust program, I felt Muse Spark should have no trouble. I had a fairly simple task I wanted done.

I set up the model in OpenCode with OpenRouter. I had to verify that I am indeed at least 18 years of age before it would allow me to continue. I then issued my prompt to Muse Spark and it set about its work.

Muse Spark successfully completed my task, but:

• It took 2 prompts for a relatively simple fix—I am unsure whether my prompt was not clear, or if Muse Spark was trained to do the minimum possible work to fix something.

• The changes it made were correct and matched what I wanted (after the second prompt).

• Using Muse Spark was easier than doing the code myself, and it cost 33 cents.

This might not have been a great test, as I had an exact fix in mind, but Muse Spark performed well. It seems to be terse and doesn't chat endlessly about nonsense, which I appreciated. It finished with the statement "No match or if" instead of a 500-word essay.

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