Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
61
ZAYA1-8B
62
Pick ZAYA1-8B if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you need the larger 400K context window.
Knowledge
+19.9 difference
GPT-5.4 nano
ZAYA1-8B
$0.2 / $1.25
$0 / $0
191 t/s
N/A
3.64s
N/A
400K
131K
Pick ZAYA1-8B if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you need the larger 400K context window.
ZAYA1-8B finishes one point ahead on BenchLM's provisional leaderboard, 62 to 61. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
ZAYA1-8B's sharpest advantage is in knowledge, where it averages 73.1 against 53.2. The single biggest benchmark swing on the page is GPQA, 82.8% to 71%.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 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. GPT-5.4 nano gives you the larger context window at 400K, compared with 131K for ZAYA1-8B.
ZAYA1-8B is ahead on BenchLM's provisional leaderboard, 62 to 61. The biggest single separator in this matchup is GPQA, where the scores are 82.8% and 71%.
ZAYA1-8B has the edge for knowledge tasks in this comparison, averaging 73.1 versus 53.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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