Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
76
Interfaze Beta
77
Verified leaderboard positions: Claude Opus 4.5 #16 · Interfaze Beta unranked
Pick Interfaze Beta if you want the stronger benchmark profile. Claude Opus 4.5 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+23.7 difference
Multimodal
+1.1 difference
Claude Opus 4.5
Interfaze Beta
$5 / $25
$1.5 / $3.5
46 t/s
N/A
1.01s
N/A
200K
1M
Pick Interfaze Beta if you want the stronger benchmark profile. Claude Opus 4.5 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Interfaze Beta finishes one point ahead on BenchLM's provisional leaderboard, 77 to 76. 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.
Interfaze Beta's sharpest advantage is in knowledge, where it averages 89.9 against 66.2. The single biggest benchmark swing on the page is GPQA, 87% to 89.9%.
Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.50 input / $3.50 output per 1M tokens for Interfaze Beta. That is roughly 7.1x on output cost alone. Interfaze Beta is the reasoning model in the pair, while Claude Opus 4.5 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. Interfaze Beta gives you the larger context window at 1M, compared with 200K for Claude Opus 4.5.
Interfaze Beta is ahead on BenchLM's provisional leaderboard, 77 to 76. The biggest single separator in this matchup is GPQA, where the scores are 87% and 89.9%.
Interfaze Beta has the edge for knowledge tasks in this comparison, averaging 89.9 versus 66.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Interfaze Beta has the edge for multimodal and grounded tasks in this comparison, averaging 71.1 versus 70. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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