Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1
57
Ling 2.6 Flash
36
Pick GPT-4.1 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Coding
+27.6 difference
Knowledge
+7.3 difference
Inst. Following
+30.4 difference
GPT-4.1
Ling 2.6 Flash
$2 / $8
$null / $null
108 t/s
209.5 t/s
1.02s
1.07s
1M
262K
Pick GPT-4.1 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GPT-4.1 is clearly ahead on the provisional aggregate, 57 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in instruction following, where it averages 87.4 against 57. The single biggest benchmark swing on the page is GPQA, 66.3% to 59%.
GPT-4.1 gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.
GPT-4.1 is ahead on BenchLM's provisional leaderboard, 57 to 36. The biggest single separator in this matchup is GPQA, where the scores are 66.3% and 59%.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 59. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 54.6 versus 27. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 57. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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