Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Holo3-122B-A10B
74
Qwen3.7 Max
93
Verified leaderboard positions: Holo3-122B-A10B unranked · Qwen3.7 Max #2
Pick Qwen3.7 Max if you want the stronger benchmark profile. Holo3-122B-A10B only becomes the better choice if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+9.2 difference
Holo3-122B-A10B
Qwen3.7 Max
$null / $null
$null / $null
N/A
N/A
N/A
N/A
64K
1M
Pick Qwen3.7 Max if you want the stronger benchmark profile. Holo3-122B-A10B only becomes the better choice if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Qwen3.7 Max is clearly ahead on the provisional aggregate, 93 to 74. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.7 Max 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. Qwen3.7 Max gives you the larger context window at 1M, compared with 64K for Holo3-122B-A10B.
Qwen3.7 Max is ahead on BenchLM's provisional leaderboard, 93 to 74.
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 69.7. Qwen3.7 Max stays close enough that the answer can still flip depending on your workload.
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