Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro
71
Qwen3.5-122B-A10B
66
Verified leaderboard positions: DeepSeek V4 Pro #22 · Qwen3.5-122B-A10B #7
Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Qwen3.5-122B-A10B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Agentic
+3.0 difference
Coding
+13.2 difference
Knowledge
+32.2 difference
DeepSeek V4 Pro
Qwen3.5-122B-A10B
$1.74 / $3.48
$0 / $0
N/A
N/A
N/A
N/A
1M
262K
Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Qwen3.5-122B-A10B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
DeepSeek V4 Pro is clearly ahead on the provisional aggregate, 71 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Pro's sharpest advantage is in agentic, where it averages 59.1 against 56.1. The single biggest benchmark swing on the page is GPQA, 72.9% to 86.6%. Qwen3.5-122B-A10B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
DeepSeek V4 Pro is also the more expensive model on tokens at $1.74 input / $3.48 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-122B-A10B. That is roughly Infinityx on output cost alone. Qwen3.5-122B-A10B is the reasoning model in the pair, while DeepSeek V4 Pro 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 gives you the larger context window at 1M, compared with 262K for Qwen3.5-122B-A10B.
DeepSeek V4 Pro is ahead on BenchLM's provisional leaderboard, 71 to 66. The biggest single separator in this matchup is GPQA, where the scores are 72.9% and 86.6%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 49.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 72 versus 58.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro has the edge for agentic tasks in this comparison, averaging 59.1 versus 56.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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