Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Holo3-35B-A3B
75
Kimi K2.5 (Reasoning)
76
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Holo3-35B-A3B 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
+28.0 difference
Holo3-35B-A3B
Kimi K2.5 (Reasoning)
$null / $null
$0.6 / $3
N/A
N/A
N/A
N/A
64K
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Holo3-35B-A3B 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.
Kimi K2.5 (Reasoning) finishes one point ahead on BenchLM's provisional leaderboard, 76 to 75. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Kimi K2.5 (Reasoning) is the reasoning model in the pair, while Holo3-35B-A3B 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. Kimi K2.5 (Reasoning) gives you the larger context window at 128K, compared with 64K for Holo3-35B-A3B.
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 76 to 75.
Holo3-35B-A3B has the edge for agentic tasks in this comparison, averaging 82.6 versus 54.6. Kimi K2.5 (Reasoning) stays close enough that the answer can still flip depending on your workload.
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