Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
65
Kimi K2.5 (Reasoning)
76
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Coding
+35.2 difference
Knowledge
+26.0 difference
Multimodal
+1.6 difference
Gemma 4 31B
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 31B 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 65. 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 coding, where it averages 76.8 against 41.6. The single biggest benchmark swing on the page is GPQA, 84.3% to 87.6%.
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 31B. That is roughly Infinityx on output cost alone. Gemma 4 31B 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 65. The biggest single separator in this matchup is GPQA, where the scores are 84.3% and 87.6%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 61.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 41.6. Gemma 4 31B stays close enough that the answer can still flip depending on your workload.
Kimi K2.5 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 76.9. 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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