Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 26B A4B
58
Ling 2.6 Flash
44
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Knowledge
+9.8 difference
Gemma 4 26B A4B
Ling 2.6 Flash
$0 / $0
$0.1 / $0.3
N/A
209.5 t/s
N/A
1.07s
256K
262K
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Gemma 4 26B A4B is clearly ahead on the provisional aggregate, 58 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ling 2.6 Flash is also the more expensive model on tokens at $0.10 input / $0.30 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 26B A4B. That is roughly Infinityx on output cost alone. Gemma 4 26B A4B 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 26B A4B.
Gemma 4 26B A4B is ahead on BenchLM's provisional leaderboard, 58 to 44.
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 49.2. Gemma 4 26B A4B stays close enough that the answer can still flip depending on your workload.
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