Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1
57
ZAYA1-74B-Preview
54
Pick GPT-4.1 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Coding
+1.4 difference
Knowledge
+2.0 difference
GPT-4.1
ZAYA1-74B-Preview
$2 / $8
$0 / $0
108 t/s
N/A
1.02s
N/A
1M
256K
Pick GPT-4.1 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
GPT-4.1 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.
GPT-4.1's sharpest advantage is in knowledge, where it averages 66.3 against 64.3. The single biggest benchmark swing on the page is GPQA, 66.3% to 57.3%.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 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 is the reasoning model in the pair, while GPT-4.1 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. GPT-4.1 gives you the larger context window at 1M, compared with 256K for ZAYA1-74B-Preview.
GPT-4.1 is ahead on BenchLM's provisional leaderboard, 57 to 54. The biggest single separator in this matchup is GPQA, where the scores are 66.3% and 57.3%.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 64.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 54.6 versus 53.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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