Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
66
Ling 2.6 Flash
44
Pick Gemini 2.5 Pro 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.
Coding
+36.8 difference
Knowledge
+18.2 difference
Gemini 2.5 Pro
Ling 2.6 Flash
$1.25 / $5
$0.1 / $0.3
117 t/s
209.5 t/s
21.19s
1.07s
1M
262K
Pick Gemini 2.5 Pro 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.
Gemini 2.5 Pro is clearly ahead on the provisional aggregate, 66 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Pro's sharpest advantage is in coding, where it averages 63.8 against 27. The single biggest benchmark swing on the page is GPQA, 83% to 59%. Ling 2.6 Flash does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.10 input / $0.30 output per 1M tokens for Ling 2.6 Flash. That is roughly 16.7x on output cost alone. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.
Gemini 2.5 Pro is ahead on BenchLM's provisional leaderboard, 66 to 44. The biggest single separator in this matchup is GPQA, where the scores are 83% and 59%.
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 40.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 27. Ling 2.6 Flash stays close enough that the answer can still flip depending on your workload.
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