Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Qwen3 235B 2507
35
Qwen3.6-27B
72
Verified leaderboard positions: Qwen3 235B 2507 unranked · Qwen3.6-27B #10
Pick Qwen3.6-27B if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+14.0 difference
Qwen3 235B 2507
Qwen3.6-27B
$0 / $0
$0 / $0
N/A
N/A
N/A
N/A
128K
262K
Pick Qwen3.6-27B if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.6-27B is clearly ahead on the provisional aggregate, 72 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-27B is the reasoning model in the pair, while Qwen3 235B 2507 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. Qwen3.6-27B gives you the larger context window at 262K, compared with 128K for Qwen3 235B 2507.
Qwen3.6-27B is ahead on BenchLM's provisional leaderboard, 72 to 35. The biggest single separator in this matchup is GPQA, where the scores are 77.5% and 87.8%.
Qwen3 235B 2507 has the edge for knowledge tasks in this comparison, averaging 76.2 versus 62.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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