Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
45
Ling 2.6 Flash
36
Pick GPT-4.1 mini if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if coding is the priority.
Coding
+3.4 difference
Knowledge
+5.2 difference
Inst. Following
+31.5 difference
GPT-4.1 mini
Ling 2.6 Flash
$0.4 / $1.6
$null / $null
80 t/s
209.5 t/s
0.76s
1.07s
1M
262K
Pick GPT-4.1 mini if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if coding is the priority.
GPT-4.1 mini is clearly ahead on the provisional aggregate, 45 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1 mini's sharpest advantage is in instruction following, where it averages 88.5 against 57. The single biggest benchmark swing on the page is GPQA, 64.2% to 59%. Ling 2.6 Flash does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.
GPT-4.1 mini is ahead on BenchLM's provisional leaderboard, 45 to 36. The biggest single separator in this matchup is GPQA, where the scores are 64.2% and 59%.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 64.2 versus 59. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Ling 2.6 Flash has the edge for coding in this comparison, averaging 27 versus 23.6. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 57. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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