Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.6
85
ZAYA1-74B-Preview
58
Verified leaderboard positions: Kimi K2.6 #6 · ZAYA1-74B-Preview unranked
Pick Kimi K2.6 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+18.8 difference
Knowledge
+10.5 difference
Kimi K2.6
ZAYA1-74B-Preview
$0.95 / $4
$0 / $0
N/A
N/A
N/A
N/A
256K
256K
Pick Kimi K2.6 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Kimi K2.6 is clearly ahead on the provisional aggregate, 85 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.6's sharpest advantage is in coding, where it averages 72 against 53.2. The single biggest benchmark swing on the page is GPQA, 90.5% to 57.3%. ZAYA1-74B-Preview does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for ZAYA1-74B-Preview. That is roughly Infinityx on output cost alone.
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 85 to 58. The biggest single separator in this matchup is GPQA, where the scores are 90.5% and 57.3%.
ZAYA1-74B-Preview has the edge for knowledge tasks in this comparison, averaging 64.3 versus 53.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for coding in this comparison, averaging 72 versus 53.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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