Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude 4.1 Opus
51
Ornith-1.0-397B
96
Pick Ornith-1.0-397B if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+7.9 difference
Claude 4.1 Opus
Ornith-1.0-397B
$15 / $75
$0 / $0
29 t/s
N/A
1.66s
N/A
200K
262K
Pick Ornith-1.0-397B if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Ornith-1.0-397B is clearly ahead on the provisional aggregate, 96 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ornith-1.0-397B's sharpest advantage is in coding, where it averages 82.4 against 74.5. The single biggest benchmark swing on the page is SWE-bench Verified, 74.5% to 82.4%.
Claude 4.1 Opus is also the more expensive model on tokens at $15.00 input / $75.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-397B. That is roughly Infinityx on output cost alone. Ornith-1.0-397B is the reasoning model in the pair, while Claude 4.1 Opus 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. Ornith-1.0-397B gives you the larger context window at 262K, compared with 200K for Claude 4.1 Opus.
Ornith-1.0-397B is ahead on BenchLM's provisional leaderboard, 96 to 51. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 74.5% and 82.4%.
Ornith-1.0-397B has the edge for coding in this comparison, averaging 82.4 versus 74.5. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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