Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Laguna M.1
43
Ornith-1.0-9B
52
Pick Ornith-1.0-9B if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+2.4 difference
Coding
+13.0 difference
Laguna M.1
Ornith-1.0-9B
$0.2 / $0.4
$0 / $0
N/A
N/A
N/A
N/A
256K
262K
Pick Ornith-1.0-9B if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Ornith-1.0-9B is clearly ahead on the provisional aggregate, 52 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ornith-1.0-9B's sharpest advantage is in coding, where it averages 69.4 against 56.4. The single biggest benchmark swing on the page is SWE-bench Verified, 72.5% to 69.4%.
Laguna M.1 is also the more expensive model on tokens at $0.20 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-9B. That is roughly Infinityx on output cost alone. Ornith-1.0-9B gives you the larger context window at 262K, compared with 256K for Laguna M.1.
Ornith-1.0-9B is ahead on BenchLM's provisional leaderboard, 52 to 43. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 72.5% and 69.4%.
Ornith-1.0-9B has the edge for coding in this comparison, averaging 69.4 versus 56.4. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Ornith-1.0-9B has the edge for agentic tasks in this comparison, averaging 43.1 versus 40.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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