Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 26B A4B
55
Kimi K2.5 (Reasoning)
76
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Knowledge
+38.1 difference
Multimodal
+4.7 difference
Gemma 4 26B A4B
Kimi K2.5 (Reasoning)
$0 / $0
$0.6 / $3
N/A
N/A
N/A
N/A
256K
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Kimi K2.5 (Reasoning) is clearly ahead on the provisional aggregate, 76 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in knowledge, where it averages 87.3 against 49.2. The single biggest benchmark swing on the page is MMMU-Pro, 73.8% to 78.5%.
Kimi K2.5 (Reasoning) is also the more expensive model on tokens at $0.60 input / $3.00 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 gives you the larger context window at 256K, compared with 128K for Kimi K2.5 (Reasoning).
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 76 to 55. The biggest single separator in this matchup is MMMU-Pro, where the scores are 73.8% and 78.5%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 49.2. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 73.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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