What would be the IQ and other benchmarks of o3 that uses $1 million worth of compute resources to answer one question?

Aggregating from independent reasoning traces is a well-known technique that helps somewhat but quickly plateaus, which is the reason o1/o3 are an important innovation, they use additional tokens much more efficiently and reach greater capability, as long as those tokens are within a single reasoning trace. Once a trace is done, more compute can only go to consensus or best-of-k aggregation from multiple traces, which is more wasteful in compute and quickly plateaus.

The $4000 high resource config of o3 for ARC-AGI was using 1024 traces of about 55K tokens, the same length as with the low resource config that runs 6 traces. Possibly longer reasoning traces don't work yet, otherwise a pour money on the problem option would've used longer traces. So a million dollar config would just use 250K reasoning traces of length 55K, which is probably slightly better than what 1K traces produce already.