Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Sonnet 4.5
67
Qwen3.6-27B
72
Verified leaderboard positions: Claude Sonnet 4.5 unranked · Qwen3.6-27B #10
Pick Qwen3.6-27B if you want the stronger benchmark profile. Claude Sonnet 4.5 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+4.0 difference
Coding
+6.6 difference
Knowledge
+21.2 difference
Claude Sonnet 4.5
Qwen3.6-27B
$3 / $15
$0 / $0
N/A
N/A
N/A
N/A
200K
262K
Pick Qwen3.6-27B if you want the stronger benchmark profile. Claude Sonnet 4.5 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.6-27B is clearly ahead on the provisional aggregate, 72 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-27B's sharpest advantage is in agentic, where it averages 59.3 against 55.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 50% to 59.3%. Claude Sonnet 4.5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Sonnet 4.5 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while Claude Sonnet 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 Sonnet 4.5.
Qwen3.6-27B is ahead on BenchLM's provisional leaderboard, 72 to 67. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 50% and 59.3%.
Claude Sonnet 4.5 has the edge for knowledge tasks in this comparison, averaging 83.4 versus 62.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude Sonnet 4.5 has the edge for coding in this comparison, averaging 77.2 versus 70.6. Qwen3.6-27B stays close enough that the answer can still flip depending on your workload.
Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 55.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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