Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro Base
43
Qwen3.5-27B
64
Verified leaderboard positions: DeepSeek V4 Pro Base unranked · Qwen3.5-27B #15
Pick Qwen3.5-27B if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if multilingual is the priority or you need the larger 1M context window.
Reasoning
+9.1 difference
Knowledge
+17.2 difference
Multilingual
+2.2 difference
DeepSeek V4 Pro Base
Qwen3.5-27B
$null / $null
$0 / $0
N/A
N/A
N/A
N/A
1M
262K
Pick Qwen3.5-27B if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if multilingual is the priority or you need the larger 1M context window.
Qwen3.5-27B is clearly ahead on the provisional aggregate, 64 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5-27B's sharpest advantage is in knowledge, where it averages 80.6 against 63.4. The single biggest benchmark swing on the page is MMLU-Pro, 73.5% to 86.1%. DeepSeek V4 Pro Base does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
Qwen3.5-27B is the reasoning model in the pair, while DeepSeek V4 Pro Base 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. DeepSeek V4 Pro Base gives you the larger context window at 1M, compared with 262K for Qwen3.5-27B.
Qwen3.5-27B is ahead on BenchLM's provisional leaderboard, 64 to 43. The biggest single separator in this matchup is MMLU-Pro, where the scores are 73.5% and 86.1%.
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 80.6 versus 63.4. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for reasoning in this comparison, averaging 60.6 versus 51.5. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro Base has the edge for multilingual tasks in this comparison, averaging 84.4 versus 82.2. Qwen3.5-27B stays close enough that the answer can still flip depending on your workload.
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