Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Qwen3.5-27B
62
Qwen3.6-35B-A3B
66
Verified leaderboard positions: Qwen3.5-27B #19 · Qwen3.6-35B-A3B #23
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Qwen3.5-27B only becomes the better choice if knowledge is the priority.
Agentic
+0.1 difference
Coding
+3.9 difference
Knowledge
+20.1 difference
Qwen3.5-27B
Qwen3.6-35B-A3B
$0 / $0
N/A
N/A
N/A
N/A
N/A
262K
262K
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Qwen3.5-27B only becomes the better choice if knowledge is the priority.
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 66 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B's sharpest advantage is in coding, where it averages 66.9 against 63. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 41.6% to 51.5%. Qwen3.5-27B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 66 to 62. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 41.6% and 51.5%.
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 80.6 versus 60.5. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 66.9 versus 63. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for agentic tasks in this comparison, averaging 51.6 versus 51.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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