Head-to-head comparison across 5benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Muse Spark
82
Qwen3.5 397B
64
Verified leaderboard positions: Muse Spark unranked · Qwen3.5 397B #17
Pick Muse Spark if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if reasoning is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+2.8 difference
Coding
+1.4 difference
Reasoning
+20.7 difference
Knowledge
+14.8 difference
Multimodal
+2.6 difference
Muse Spark
Qwen3.5 397B
N/A
$0.6 / $3.6
N/A
96 t/s
N/A
2.44s
262K
128K
Pick Muse Spark if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if reasoning is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Muse Spark is clearly ahead on the provisional aggregate, 82 to 64. 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 agentic, where it averages 59 against 56.2. The single biggest benchmark swing on the page is HLE, 50.4% to 28.7%. Qwen3.5 397B does hit back in reasoning, 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 Qwen3.5 397B 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. Muse Spark gives you the larger context window at 262K, compared with 128K for Qwen3.5 397B.
Muse Spark is ahead on BenchLM's provisional leaderboard, 82 to 64. The biggest single separator in this matchup is HLE, where the scores are 50.4% and 28.7%.
Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 65.2 versus 50.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Muse Spark has the edge for coding in this comparison, averaging 61.7 versus 60.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 63.2 versus 42.5. Inside this category, AA-LCR is the benchmark that creates the most daylight between them.
Muse Spark has the edge for agentic tasks in this comparison, averaging 59 versus 56.2. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Muse Spark has the edge for multimodal and grounded tasks in this comparison, averaging 82.2 versus 79.6. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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