Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
o1
57
ZAYA1-74B-Preview
54
Pick o1 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Knowledge
+11.4 difference
o1
ZAYA1-74B-Preview
$15 / $60
$0 / $0
98 t/s
N/A
32.29s
N/A
200K
256K
Pick o1 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
o1 has the cleaner provisional overall profile here, landing at 57 versus 54. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
o1's sharpest advantage is in knowledge, where it averages 75.7 against 64.3. The single biggest benchmark swing on the page is GPQA, 75.7% to 57.3%.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 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. ZAYA1-74B-Preview gives you the larger context window at 256K, compared with 200K for o1.
o1 is ahead on BenchLM's provisional leaderboard, 57 to 54. The biggest single separator in this matchup is GPQA, where the scores are 75.7% and 57.3%.
o1 has the edge for knowledge tasks in this comparison, averaging 75.7 versus 64.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.