Head-to-head comparison across 6benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
77
Qwen3.5-27B
63
Verified leaderboard positions: Claude Opus 4.5 #9 · Qwen3.5-27B #16
Pick Claude Opus 4.5 if you want the stronger benchmark profile. Qwen3.5-27B only becomes the better choice if instruction following is the priority or you want the cheaper token bill.
Agentic
+10.9 difference
Coding
+2.9 difference
Reasoning
+3.8 difference
Knowledge
+14.4 difference
Multilingual
+3.5 difference
Inst. Following
+15.6 difference
Claude Opus 4.5
Qwen3.5-27B
$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. Qwen3.5-27B only becomes the better choice if instruction following is the priority or you want the cheaper token bill.
Claude Opus 4.5 is clearly ahead on the provisional aggregate, 77 to 63. 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 51.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 59.3% to 41.6%. Qwen3.5-27B does hit back in instruction following, 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 Qwen3.5-27B. That is roughly Infinityx on output cost alone. Qwen3.5-27B 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. Qwen3.5-27B 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 63. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 59.3% and 41.6%.
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 80.6 versus 66.2. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for coding in this comparison, averaging 65.9 versus 63. 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 60.6. 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 51.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for instruction following in this comparison, averaging 95 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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