Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5
91
Ling 2.6 Flash
36
Verified leaderboard positions: GPT-5.5 #5 · Ling 2.6 Flash unranked
Pick GPT-5.5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+31.6 difference
Knowledge
+7.4 difference
GPT-5.5
Ling 2.6 Flash
$5 / $30
$null / $null
N/A
209.5 t/s
N/A
1.07s
1M
262K
Pick GPT-5.5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.5 is clearly ahead on the provisional aggregate, 91 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5's sharpest advantage is in coding, where it averages 58.6 against 27. The single biggest benchmark swing on the page is GPQA, 93.6% to 59%.
GPT-5.5 is the reasoning model in the pair, while Ling 2.6 Flash 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-5.5 gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.
GPT-5.5 is ahead on BenchLM's provisional leaderboard, 91 to 36. The biggest single separator in this matchup is GPQA, where the scores are 93.6% and 59%.
GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 59. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for coding in this comparison, averaging 58.6 versus 27. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
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