Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 26B A4B
58
Qwen3.6-27B
72
Verified leaderboard positions: Gemma 4 26B A4B unranked · Qwen3.6-27B #10
Pick Qwen3.6-27B if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Knowledge
+13.0 difference
Multimodal
+2.0 difference
Gemma 4 26B A4B
Qwen3.6-27B
$0 / $0
$0 / $0
N/A
N/A
N/A
N/A
256K
262K
Pick Qwen3.6-27B if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Qwen3.6-27B is clearly ahead on the provisional aggregate, 72 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-27B's sharpest advantage is in knowledge, where it averages 62.2 against 49.2. The single biggest benchmark swing on the page is HLE, 17.2% to 24%.
Qwen3.6-27B gives you the larger context window at 262K, compared with 256K for Gemma 4 26B A4B.
Qwen3.6-27B is ahead on BenchLM's provisional leaderboard, 72 to 58. The biggest single separator in this matchup is HLE, where the scores are 17.2% and 24%.
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 62.2 versus 49.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 75.8 versus 73.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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