Head-to-head comparison across 7benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
77
Qwen3.5-122B-A10B
65
Verified leaderboard positions: Claude Opus 4.5 #9 · Qwen3.5-122B-A10B #8
Pick Claude Opus 4.5 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
+6.4 difference
Coding
+6.1 difference
Reasoning
+4.2 difference
Knowledge
+15.4 difference
Multilingual
+3.5 difference
Multimodal
+7.2 difference
Inst. Following
+14.0 difference
Claude Opus 4.5
Qwen3.5-122B-A10B
$5 / $25
$0 / $0
46 t/s
N/A
1.01s
N/A
200K
262K
Pick Claude Opus 4.5 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.
Claude Opus 4.5 is clearly ahead on the provisional aggregate, 77 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.5's sharpest advantage is in agentic, where it averages 62.5 against 56.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 59.3% to 49.4%. 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.
Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 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 Opus 4.5 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 Opus 4.5.
Claude Opus 4.5 is ahead on BenchLM's provisional leaderboard, 77 to 65. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 59.3% and 49.4%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 66.2. Inside this category, SuperGPQA 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 65.9. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for reasoning in this comparison, averaging 64.4 versus 60.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 62.5 versus 56.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 77.2 versus 70. Inside this category, V* is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for instruction following in this comparison, averaging 93.4 versus 79.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for multilingual tasks in this comparison, averaging 85.7 versus 82.2. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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