Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude 4.1 Opus
52
Qwen3.5-122B-A10B
65
Verified leaderboard positions: Claude 4.1 Opus unranked · Qwen3.5-122B-A10B #8
Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+2.5 difference
Claude 4.1 Opus
Qwen3.5-122B-A10B
$15 / $75
$0 / $0
29 t/s
N/A
1.66s
N/A
200K
262K
Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.5-122B-A10B is clearly ahead on the provisional aggregate, 65 to 52. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 4.1 Opus is also the more expensive model on tokens at $15.00 input / $75.00 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 Claude 4.1 Opus 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. Qwen3.5-122B-A10B gives you the larger context window at 262K, compared with 200K for Claude 4.1 Opus.
Qwen3.5-122B-A10B is ahead on BenchLM's provisional leaderboard, 65 to 52. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 74.5% and 72%.
Claude 4.1 Opus has the edge for coding in this comparison, averaging 74.5 versus 72. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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