Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
75
Ornith-1.0-35B
67
Verified leaderboard positions: Claude Opus 4.5 #16 · Ornith-1.0-35B unranked
Pick Claude Opus 4.5 if you want the stronger benchmark profile. Ornith-1.0-35B only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Agentic
+1.7 difference
Claude Opus 4.5
Ornith-1.0-35B
$5 / $25
$0 / $0
46 t/s
N/A
1.01s
N/A
200K
262K
Pick Claude Opus 4.5 if you want the stronger benchmark profile. Ornith-1.0-35B only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Claude Opus 4.5 is clearly ahead on the provisional aggregate, 75 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-35B. That is roughly Infinityx on output cost alone. Ornith-1.0-35B 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. Ornith-1.0-35B gives you the larger context window at 262K, compared with 200K for Claude Opus 4.5.
Claude Opus 4.5 is ahead on BenchLM's provisional leaderboard, 75 to 67. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 59.3% and 64.2%.
Ornith-1.0-35B has the edge for agentic tasks in this comparison, averaging 64.2 versus 62.5. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
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