Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
80
Qwen3.6-27B
72
Verified leaderboard positions: Claude Opus 4.5 #7 · Qwen3.6-27B #10
Pick Claude Opus 4.5 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if multimodal & grounded is the priority or you need the larger 262K context window.
Agentic
+3.2 difference
Coding
+4.7 difference
Knowledge
+4.0 difference
Multimodal
+5.2 difference
Claude Opus 4.5
Qwen3.6-27B
$null / $null
$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. Qwen3.6-27B only becomes the better choice if multimodal & grounded is the priority or you need the larger 262K context window.
Claude Opus 4.5 is clearly ahead on the provisional aggregate, 80 to 72. 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 knowledge, where it averages 66.2 against 62.2. The single biggest benchmark swing on the page is HLE, 30.8% to 24%. Qwen3.6-27B does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Qwen3.6-27B 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. Qwen3.6-27B 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, 80 to 72. The biggest single separator in this matchup is HLE, where the scores are 30.8% and 24%.
Claude Opus 4.5 has the edge for knowledge tasks in this comparison, averaging 66.2 versus 62.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
Qwen3.6-27B has the edge for coding in this comparison, averaging 70.6 versus 65.9. Inside this category, NL2Repo 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 59.3. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 75.8 versus 70.6. Inside this category, V* is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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