Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5 (Reasoning)
75
Ornith-1.0-397B
96
Pick Ornith-1.0-397B if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+22.9 difference
Coding
+5.6 difference
Kimi K2.5 (Reasoning)
Ornith-1.0-397B
$0.6 / $3
$0 / $0
N/A
N/A
N/A
N/A
128K
262K
Pick Ornith-1.0-397B if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Ornith-1.0-397B is clearly ahead on the provisional aggregate, 96 to 75. 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 agentic, where it averages 77.5 against 54.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 50.8% to 77.5%.
Kimi K2.5 (Reasoning) is also the more expensive model on tokens at $0.60 input / $3.00 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 gives you the larger context window at 262K, compared with 128K for Kimi K2.5 (Reasoning).
Ornith-1.0-397B is ahead on BenchLM's provisional leaderboard, 96 to 75. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 50.8% and 77.5%.
Ornith-1.0-397B has the edge for coding in this comparison, averaging 82.4 versus 76.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Ornith-1.0-397B has the edge for agentic tasks in this comparison, averaging 77.5 versus 54.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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