Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.6
87
ZAYA1-8B
62
Verified leaderboard positions: Claude Opus 4.6 #4 · ZAYA1-8B unranked
Pick Claude Opus 4.6 if you want the stronger benchmark profile. ZAYA1-8B only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Knowledge
+3.1 difference
Claude Opus 4.6
ZAYA1-8B
$5 / $25
$0 / $0
40 t/s
N/A
1.78s
N/A
1M
131K
Pick Claude Opus 4.6 if you want the stronger benchmark profile. ZAYA1-8B only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Claude Opus 4.6 is clearly ahead on the provisional aggregate, 87 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.6's sharpest advantage is in knowledge, where it averages 76.2 against 73.1. The single biggest benchmark swing on the page is GPQA, 91.3% to 71%.
Claude Opus 4.6 is also the more expensive model on tokens at $5.00 input / $25.00 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 is the reasoning model in the pair, while Claude Opus 4.6 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Opus 4.6 gives you the larger context window at 1M, compared with 131K for ZAYA1-8B.
Claude Opus 4.6 is ahead on BenchLM's provisional leaderboard, 87 to 62. The biggest single separator in this matchup is GPQA, where the scores are 91.3% and 71%.
Claude Opus 4.6 has the edge for knowledge tasks in this comparison, averaging 76.2 versus 73.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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