Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
36
Qwen3.5-35B-A3B
56
Verified leaderboard positions: DeepSeek V3 unranked · Qwen3.5-35B-A3B #18
Pick Qwen3.5-35B-A3B if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+19.2 difference
Knowledge
+9.3 difference
Inst. Following
+5.8 difference
DeepSeek V3
Qwen3.5-35B-A3B
$0.27 / $1.1
$0 / $0
N/A
N/A
N/A
N/A
128K
262K
Pick Qwen3.5-35B-A3B if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.5-35B-A3B is clearly ahead on the provisional aggregate, 56 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5-35B-A3B's sharpest advantage is in coding, where it averages 58.4 against 39.2. The single biggest benchmark swing on the page is SWE-bench Verified, 42% to 69.2%.
DeepSeek V3 is also the more expensive model on tokens at $0.27 input / $1.10 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-A3B is the reasoning model in the pair, while DeepSeek V3 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. Qwen3.5-35B-A3B gives you the larger context window at 262K, compared with 128K for DeepSeek V3.
Qwen3.5-35B-A3B is ahead on BenchLM's provisional leaderboard, 56 to 36. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 42% and 69.2%.
Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 79.3 versus 70. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for coding in this comparison, averaging 58.4 versus 39.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for instruction following in this comparison, averaging 91.9 versus 86.1. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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