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o1-pro vs ReMM SLERP 13B

ReMM SLERP 13B costs 923.1x less per output token than o1-pro ($0.65 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 ReMM SLERP 13BUndi95
Coding
No data
Overall
No data
Output $/M
$0.65
vs $600.00 vs $0.65 per 1M output tokens. ReMM SLERP 13B is 923.1x cheaper.

o1-pro or ReMM SLERP 13B: which to pick

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

Pick o1-pro for a larger context window (200K against 6K tokens).

No benchmark has tested both yet. o1-pro has results on AA Intelligence Index and ARC-AGI; ReMM SLERP 13B 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, ReMM SLERP 13B 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 ReMM SLERP 13B $0.65 per million output tokens, 923.1x apart.
Context window
o1-pro takes 200K tokens, ReMM SLERP 13B 6K.

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 ReMM SLERP 13B
Benchmarko1-proReMM SLERP 13BLeader
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 ReMM SLERP 13B
Benchmarko1-proReMM SLERP 13BLeader
ARC-AGI23.3%Not measuredOnly o1-pro measured
Neither model has a result on the other 22 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
ReMM SLERP 13B$0.0007Fits in one request

ReMM SLERP 13B costs less

Repository review

50K input + 3K output tokens

o1-pro$9.30Fits in one request
ReMM SLERP 13B$0.019Exceeds the context window

ReMM SLERP 13B costs less

Agent loop

200K input + 10K output tokens

o1-pro$36.00Exceeds the context window
ReMM SLERP 13B$0.076Exceeds the context window

ReMM SLERP 13B 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 ReMM SLERP 13B
SpecificationOpenAI o1-proReMM SLERP 13B
MakerOpenAIUndi95
WeightsNo public weights listedOpen weights
ReleasedMarch 19, 2025July 22, 2023
Context window200K6K
Input $/Mtok$150.00$0.35
Output $/Mtok$600.00$0.65
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is o1-pro better than ReMM SLERP 13B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick o1-pro for a larger context window (200K against 6K tokens).

Which is cheaper, o1-pro or ReMM SLERP 13B?

o1-pro costs $150.00 per million input tokens and $600.00 per million output tokens; ReMM SLERP 13B costs $0.35 and $0.65. Cost per solved task is known for neither of them.

Which has the bigger context window, o1-pro or ReMM SLERP 13B?

o1-pro, with 200K tokens against 6K.

Has any benchmark tested both o1-pro and ReMM SLERP 13B?

No benchmark has tested both yet. o1-pro has results on AA Intelligence Index and ARC-AGI; ReMM SLERP 13B has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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