Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5 Pro
100
Holo3-122B-A10B
100
Treat this as a split decision. GPT-5.5 Pro makes more sense if agentic is the priority or you need the larger 1M context window; Holo3-122B-A10B is the better fit if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+11.2 difference
GPT-5.5 Pro
Holo3-122B-A10B
$30 / $180
$0.4 / $3
N/A
N/A
N/A
N/A
1M
64K
Treat this as a split decision. GPT-5.5 Pro makes more sense if agentic is the priority or you need the larger 1M context window; Holo3-122B-A10B is the better fit if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.5 Pro and Holo3-122B-A10B finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.40 input / $3.00 output per 1M tokens for Holo3-122B-A10B. That is roughly 60.0x on output cost alone. GPT-5.5 Pro 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. GPT-5.5 Pro gives you the larger context window at 1M, compared with 64K for Holo3-122B-A10B.
GPT-5.5 Pro and Holo3-122B-A10B are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 78.9. Holo3-122B-A10B stays close enough that the answer can still flip depending on your workload.
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