Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
45
Qwen3.5-27B
63
Verified leaderboard positions: GPT-4.1 mini unranked · Qwen3.5-27B #16
Pick Qwen3.5-27B if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+39.4 difference
Knowledge
+16.4 difference
Inst. Following
+6.5 difference
GPT-4.1 mini
Qwen3.5-27B
$0.4 / $1.6
$0 / $0
80 t/s
N/A
0.76s
N/A
1M
262K
Pick Qwen3.5-27B if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.5-27B is clearly ahead on the provisional aggregate, 63 to 45. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5-27B's sharpest advantage is in coding, where it averages 63 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 23.6% to 72.4%.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 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 GPT-4.1 mini 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. GPT-4.1 mini gives you the larger context window at 1M, compared with 262K for Qwen3.5-27B.
Qwen3.5-27B is ahead on BenchLM's provisional leaderboard, 63 to 45. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 23.6% and 72.4%.
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 80.6 versus 64.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for coding in this comparison, averaging 63 versus 23.6. Inside this category, SWE-bench Verified 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 88.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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