Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro Base
43
Gemma 4 26B A4B
57
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Knowledge
+14.2 difference
DeepSeek V4 Pro Base
Gemma 4 26B A4B
$null / $null
$0 / $0
N/A
N/A
N/A
N/A
1M
256K
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Gemma 4 26B A4B is clearly ahead on the provisional aggregate, 57 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 26B A4B is the reasoning model in the pair, while DeepSeek V4 Pro Base 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. DeepSeek V4 Pro Base gives you the larger context window at 1M, compared with 256K for Gemma 4 26B A4B.
Gemma 4 26B A4B is ahead on BenchLM's provisional leaderboard, 57 to 43. The biggest single separator in this matchup is MMLU-Pro, where the scores are 73.5% and 82.6%.
DeepSeek V4 Pro Base has the edge for knowledge tasks in this comparison, averaging 63.4 versus 49.2. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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