Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5 (Reasoning)
76
ZAYA1-8B
62
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. ZAYA1-8B only becomes the better choice if you want the cheaper token bill or you need the larger 131K context window.
Knowledge
+14.2 difference
Kimi K2.5 (Reasoning)
ZAYA1-8B
$0.6 / $3
$0 / $0
N/A
N/A
N/A
N/A
128K
131K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. ZAYA1-8B only becomes the better choice if you want the cheaper token bill or you need the larger 131K context window.
Kimi K2.5 (Reasoning) is clearly ahead on the provisional aggregate, 76 to 62. 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 73.1. The single biggest benchmark swing on the page is GPQA, 87.6% to 71%.
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 ZAYA1-8B. That is roughly Infinityx on output cost alone. ZAYA1-8B gives you the larger context window at 131K, compared with 128K for Kimi K2.5 (Reasoning).
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 76 to 62. The biggest single separator in this matchup is GPQA, where the scores are 87.6% and 71%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 73.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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