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o1-pro vs Pareto 26.9

Pareto 26.9 costs 80.0x less per output token than o1-pro ($7.50 vs $600.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

o1-proOpenAI
Coding
No data
Overall
No data
Output $/M
$600.00
U Pareto 26.9Unbiased
Coding
No data
Overall
No data
Output $/M
$7.50
vs $600.00 vs $7.50 per 1M output tokens. Pareto 26.9 is 80.0x cheaper.

o1-pro or Pareto 26.9: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

No benchmark has tested both yet. o1-pro has results on AA Intelligence Index and ARC-AGI; Pareto 26.9 has none yet. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
o1-pro not benchmarked, Pareto 26.9 not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
o1-pro $600.00 against Pareto 26.9 $7.50 per million output tokens, 80.0x apart.
Context window
o1-pro takes 200K tokens, Pareto 26.9 262K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for o1-pro and Pareto 26.9
Benchmarko1-proPareto 26.9Leader
AA Intelligence Index12.4Not measuredOnly o1-pro measured
Neither model has a result on the other 1 board here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Reasoning benchmarks for o1-pro and Pareto 26.9
Benchmarko1-proPareto 26.9Leader
ARC-AGI23.3%Not measuredOnly o1-pro measured
Neither model has a result on the other 21 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

o1-pro$0.450Fits in one request
Pareto 26.9$0.0063Fits in one request

Pareto 26.9 costs less

Repository review

50K input + 3K output tokens

o1-pro$9.30Fits in one request
Pareto 26.9$0.147Fits in one request

Pareto 26.9 costs less

Agent loop

200K input + 10K output tokens

o1-pro$36.00Exceeds the context window
Pareto 26.9$0.575Fits in one request

Pareto 26.9 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of o1-pro and Pareto 26.9
SpecificationOpenAI o1-proPareto 26.9
MakerOpenAIUnbiased
WeightsNo public weights listedNo public weights listed
ReleasedMarch 19, 2025October 13, 2026
Context window200K262K
Input $/Mtok$150.00$2.50
Output $/Mtok$600.00$7.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is o1-pro better than Pareto 26.9 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, o1-pro or Pareto 26.9?

o1-pro costs $150.00 per million input tokens and $600.00 per million output tokens; Pareto 26.9 costs $2.50 and $7.50. Cost per solved task is known for neither of them.

Which has the bigger context window, o1-pro or Pareto 26.9?

Pareto 26.9, with 262K tokens against 200K.

Has any benchmark tested both o1-pro and Pareto 26.9?

No benchmark has tested both yet. o1-pro has results on AA Intelligence Index and ARC-AGI; Pareto 26.9 has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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