Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 mini
73
Ling 2.6 Flash
44
Pick GPT-5.4 mini if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Knowledge
+1.6 difference
GPT-5.4 mini
Ling 2.6 Flash
$0.75 / $4.5
$0.1 / $0.3
201 t/s
209.5 t/s
3.85s
1.07s
400K
262K
Pick GPT-5.4 mini if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GPT-5.4 mini is clearly ahead on the provisional aggregate, 73 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.10 input / $0.30 output per 1M tokens for Ling 2.6 Flash. That is roughly 15.0x on output cost alone. GPT-5.4 mini 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 mini gives you the larger context window at 400K, compared with 262K for Ling 2.6 Flash.
GPT-5.4 mini is ahead on BenchLM's provisional leaderboard, 73 to 44. The biggest single separator in this matchup is GPQA, where the scores are 88% and 59%.
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 57.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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