Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Holo3-122B-A10B
100
Step 3.7 Flash
72
Pick Holo3-122B-A10B if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if you need the larger 256K context window or you want the stronger reasoning-first profile.
Agentic
+13.0 difference
Holo3-122B-A10B
Step 3.7 Flash
$null / $null
$0.2 / $1.15
N/A
N/A
N/A
N/A
64K
256K
Pick Holo3-122B-A10B if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if you need the larger 256K context window or you want the stronger reasoning-first profile.
Holo3-122B-A10B is clearly ahead on the provisional aggregate, 100 to 72. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Holo3-122B-A10B's sharpest advantage is in agentic, where it averages 78.9 against 65.9.
Step 3.7 Flash is the reasoning model in the pair, while Holo3-122B-A10B 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. Step 3.7 Flash gives you the larger context window at 256K, compared with 64K for Holo3-122B-A10B.
Holo3-122B-A10B is ahead on BenchLM's provisional leaderboard, 100 to 72.
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 65.9. Step 3.7 Flash stays close enough that the answer can still flip depending on your workload.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.