Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Ling 2.6 Flash
36
ZAYA1-8B
62
Pick ZAYA1-8B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+14.1 difference
Inst. Following
+17.0 difference
Ling 2.6 Flash
ZAYA1-8B
$null / $null
$0 / $0
209.5 t/s
N/A
1.07s
N/A
262K
131K
Pick ZAYA1-8B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K context window or you would rather avoid the extra latency and token burn of a reasoning model.
ZAYA1-8B is clearly ahead on the provisional aggregate, 62 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
ZAYA1-8B's sharpest advantage is in instruction following, where it averages 74 against 57. The single biggest benchmark swing on the page is GPQA, 59% to 71%.
ZAYA1-8B 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. Ling 2.6 Flash gives you the larger context window at 262K, compared with 131K for ZAYA1-8B.
ZAYA1-8B is ahead on BenchLM's provisional leaderboard, 62 to 36. The biggest single separator in this matchup is GPQA, where the scores are 59% and 71%.
ZAYA1-8B has the edge for knowledge tasks in this comparison, averaging 73.1 versus 59. Inside this category, GPQA is the benchmark that creates the most daylight between them.
ZAYA1-8B has the edge for instruction following in this comparison, averaging 74 versus 57. Inside this category, IFBench is the benchmark that creates the most daylight between them.
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