Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Ornith-1.0-9B
52
Step 3.7 Flash
67
Pick Step 3.7 Flash if you want the stronger benchmark profile. Ornith-1.0-9B only becomes the better choice if coding is the priority or you want the cheaper token bill.
Agentic
+22.8 difference
Coding
+13.1 difference
Ornith-1.0-9B
Step 3.7 Flash
$0 / $0
$0.2 / $1.15
N/A
N/A
N/A
N/A
262K
256K
Pick Step 3.7 Flash if you want the stronger benchmark profile. Ornith-1.0-9B only becomes the better choice if coding is the priority or you want the cheaper token bill.
Step 3.7 Flash is clearly ahead on the provisional aggregate, 67 to 52. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Step 3.7 Flash's sharpest advantage is in agentic, where it averages 65.9 against 43.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 43.1% to 59.5%. Ornith-1.0-9B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Step 3.7 Flash is also the more expensive model on tokens at $0.20 input / $1.15 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 Step 3.7 Flash.
Step 3.7 Flash is ahead on BenchLM's provisional leaderboard, 67 to 52. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 43.1% and 59.5%.
Ornith-1.0-9B has the edge for coding in this comparison, averaging 69.4 versus 56.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 65.9 versus 43.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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