Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Holo3-122B-A10B
94
Hy3 Preview
59
Pick Holo3-122B-A10B if you want the stronger benchmark profile. Hy3 Preview only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Agentic
+24.5 difference
Holo3-122B-A10B
Hy3 Preview
$0.4 / $3
$0 / $0
N/A
N/A
N/A
N/A
64K
256K
Pick Holo3-122B-A10B if you want the stronger benchmark profile. Hy3 Preview only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Holo3-122B-A10B is clearly ahead on the provisional aggregate, 94 to 59. 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 54.4.
Holo3-122B-A10B is also the more expensive model on tokens at $0.40 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Hy3 Preview. That is roughly Infinityx on output cost alone. Hy3 Preview 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. Hy3 Preview 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, 94 to 59.
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 54.4. Hy3 Preview stays close enough that the answer can still flip depending on your workload.
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