Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Holo3-122B-A10B
78
Qwen3.6-35B-A3B
64
Verified leaderboard positions: Holo3-122B-A10B unranked · Qwen3.6-35B-A3B #13
Pick Holo3-122B-A10B if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if you need the larger 262K context window or you want the stronger reasoning-first profile.
Agentic
+27.4 difference
Holo3-122B-A10B
Qwen3.6-35B-A3B
$0.4 / $3
N/A
N/A
N/A
N/A
N/A
64K
262K
Pick Holo3-122B-A10B if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if you need the larger 262K context window or you want the stronger reasoning-first profile.
Holo3-122B-A10B is clearly ahead on the provisional aggregate, 78 to 64. 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 51.5.
Qwen3.6-35B-A3B 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. Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 64K for Holo3-122B-A10B.
Holo3-122B-A10B is ahead on BenchLM's provisional leaderboard, 78 to 64.
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 51.5. Qwen3.6-35B-A3B stays close enough that the answer can still flip depending on your workload.
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