Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
55
Muse Spark
69
Pick Muse Spark if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Coding
+38.1 difference
Knowledge
+13.8 difference
GPT-4.1 mini
Muse Spark
$0.4 / $1.6
N/A
80 t/s
N/A
0.76s
N/A
1M
262K
Pick Muse Spark if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Muse Spark is clearly ahead on the provisional aggregate, 69 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Muse Spark's sharpest advantage is in coding, where it averages 61.7 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 23.6% to 77.4%. GPT-4.1 mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Muse Spark is the reasoning model in the pair, while GPT-4.1 mini is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-4.1 mini gives you the larger context window at 1M, compared with 262K for Muse Spark.
Muse Spark is ahead on BenchLM's provisional leaderboard, 69 to 55. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 23.6% and 77.4%.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 64.2 versus 50.4. Muse Spark stays close enough that the answer can still flip depending on your workload.
Muse Spark has the edge for coding in this comparison, averaging 61.7 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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