Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
64
Ling 2.6 Flash
36
Pick Gemma 4 31B 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.
Coding
+14.6 difference
Knowledge
+2.3 difference
Gemma 4 31B
Ling 2.6 Flash
$0 / $0
$null / $null
N/A
209.5 t/s
N/A
1.07s
256K
262K
Pick Gemma 4 31B 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.
Gemma 4 31B is clearly ahead on the provisional aggregate, 64 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 31B's sharpest advantage is in coding, where it averages 41.6 against 27. The single biggest benchmark swing on the page is GPQA, 84.3% to 59%.
Gemma 4 31B 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 256K for Gemma 4 31B.
Gemma 4 31B is ahead on BenchLM's provisional leaderboard, 64 to 36. The biggest single separator in this matchup is GPQA, where the scores are 84.3% and 59%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 59. Inside this category, AA-GPQA Diamond is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 41.6 versus 27. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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