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Model comparison

Celeris-1 vs o1-pro

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
Celeris
N/A
No comparison
OpenAI
45.94/100
0 category wins1 category wins

Public leaderboard positions: Celeris-1 unranked (Not scored); o1-pro #141 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Celeris-1 and o1-pro share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 2 to o1-pro.

Updated July 24, 2026
Shared results
0
Celeris-1 only
1
o1-pro only
2
Comparable categories
1 / 8

Treat this as a split decision. Celeris-1 makes more sense if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model; o1-pro is the better fit if knowledge is the priority or you need the larger 200K context window.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Celeris-1 and o1-pro finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Celeris-1. That is roughly 100.0x on output cost alone. o1-pro is the reasoning model in the pair, while Celeris-1 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. o1-pro gives you the larger context window at 200K, compared with 8K for Celeris-1.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricCeleris-1o1-proComparison
Input / output priceUSD per 1M tokensCeleris-1$2 input / $6 outputo1-pro$150 input / $600 outputCeleris-1 has the lower combined listed price.
Generation speedtokens per secondCeleris-1Not availableo1-proNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenCeleris-1Not availableo1-proNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensCeleris-18Ko1-pro200Ko1-pro lists the larger context window.

Benchmark Deep Dive

Knowledgeo1-pro wins
BenchmarkCeleris-1o1-proResult
MMLU-ProSource 75.9%Not comparable
GPQASource 79%Not comparable
Artificial Analysis Intelligence IndexSource 18.9%Not comparable
Frequently Asked Questions (2)

Which is better, Celeris-1 or o1-pro?

Celeris-1 and o1-pro are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, Celeris-1 or o1-pro?

o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 75.9. Celeris-1 stays close enough that the answer can still flip depending on your workload.

Related Comparisons

Last updated: July 24, 2026

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