Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
79
Qwen3.6-27B
73
Verified leaderboard positions: GPT-5.2 unranked · Qwen3.6-27B #18
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if coding is the priority or you want the cheaper token bill.
Agentic
+4.1 difference
Coding
+5.9 difference
Knowledge
+30.2 difference
Multimodal
+3.7 difference
GPT-5.2
Qwen3.6-27B
$1.75 / $14
$0 / $0
73 t/s
N/A
130.34s
N/A
400K
262K
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-5.2 is clearly ahead on the provisional aggregate, 79 to 73. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 62.2. The single biggest benchmark swing on the page is GPQA, 92.4% to 87.8%. Qwen3.6-27B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 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. GPT-5.2 gives you the larger context window at 400K, compared with 262K for Qwen3.6-27B.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 79 to 73. The biggest single separator in this matchup is GPQA, where the scores are 92.4% and 87.8%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 62.2. Inside this category, AA-Omniscience Hallucination Rate 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 64.7. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 55.2. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.3 versus 76.6. 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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