Head-to-head comparison across 6benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Qwen3.5-35B-A3B
56
Qwen3.5 397B
64
Verified leaderboard positions: Qwen3.5-35B-A3B #18 · Qwen3.5 397B #15
Pick Qwen3.5 397B if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+5.6 difference
Coding
+1.9 difference
Reasoning
+4.2 difference
Knowledge
+14.1 difference
Multilingual
+3.7 difference
Inst. Following
+0.7 difference
Qwen3.5-35B-A3B
Qwen3.5 397B
$0 / $0
$0.6 / $3.6
N/A
96 t/s
N/A
2.44s
262K
128K
Pick Qwen3.5 397B if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Qwen3.5 397B is clearly ahead on the provisional aggregate, 64 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in agentic, where it averages 56.2 against 50.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 40.5% to 52.5%. Qwen3.5-35B-A3B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 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 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. Qwen3.5-35B-A3B gives you the larger context window at 262K, compared with 128K for Qwen3.5 397B.
Qwen3.5 397B is ahead on BenchLM's provisional leaderboard, 64 to 56. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 40.5% and 52.5%.
Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 79.3 versus 65.2. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for coding in this comparison, averaging 60.3 versus 58.4. Inside this category, SWE-bench Verified 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 59. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.2 versus 50.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for instruction following in this comparison, averaging 92.6 versus 91.9. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for multilingual tasks in this comparison, averaging 84.7 versus 81. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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