Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
59
Ling 2.6 Flash
36
Pick GPT-5.4 nano if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+5.8 difference
GPT-5.4 nano
Ling 2.6 Flash
$0.2 / $1.25
$null / $null
191 t/s
209.5 t/s
3.64s
1.07s
400K
262K
Pick GPT-5.4 nano if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.4 nano is clearly ahead on the provisional aggregate, 59 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 nano 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-5.4 nano gives you the larger context window at 400K, compared with 262K for Ling 2.6 Flash.
GPT-5.4 nano is ahead on BenchLM's provisional leaderboard, 59 to 36. The biggest single separator in this matchup is GPQA, where the scores are 82.8% and 59%.
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 53.2. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
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