Holo3-122B-A10B vs Ornith-1.0-397B

Pick Ornith-1.0-397B 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.

Ornith-1.0-397B has the cleaner provisional overall profile here, landing at 96 versus 94. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

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 Ornith-1.0-397B. That is roughly Infinityx on output cost alone. Ornith-1.0-397B 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. Ornith-1.0-397B gives you the larger context window at 262K, compared with 64K for Holo3-122B-A10B.