How does o1-pro rank among AI models?
o1-pro is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
o1-pro
No linked weightsOpenAI·#171 of 504 in the all-versions archive
o1-pro is a language model from OpenAI. It ranks #171 of 504 in ModelCap's all-versions archive, with an Index score of 54.9, modeled from public metadata, not measured. Its score range of 48.7–61.2 spans positions #136–#226. It reads up to 200K tokens of context, with no downloadable weights linked in the current source data.
Figures as of 6 Nov 2026, 20:49 UTC · download the public dataset · methodology
ModelCap Index · All-versions archive
54.9#171
Modeled from public metadata, not measured · range 48.7–61.2
Superseded by o3 Pro. It no longer holds a current-board position; its all-versions archive rank is #171.
Input
Unlisted
no listed API price
Output
Unlisted
no listed API price
Context
200K
tokens
Providers
0
endpoints
Providers
Uptime measured over the last 30 minutesNo provider is currently serving this model.
Other versions (1)
ModelCap Index · All-versions archive
Methodology54.9
Modeled from public metadata, not measured
All-versions archive
#171 of 504
- Score range
- 48.7–61.2
- Rank range
- #136–#226
Technical details
- Public rank basis
- Modeled · tier sibling (architecture)
- Evidence label
- Modeled · tier sibling · higher pro tier of o1 (53) (96%); shrunk 0.1 toward the measured corpus
- Index support
- 20.0% · limited
- Identity binding
- Exact catalogue product · openai/openai/o1-pro · aggregates disclosed benchmark configurations · endpoint configuration not claimed
- Index observations used
- 0
- Qualified Index evidence point
- 54.9
How this position was produced · fused launch placement
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
- Fused estimate
- 54.9 ± 4.9
- Independent share
- 0%
- Shrink toward corpus
- -0.1
- Optimism haircut
- None applied
- Method
- precision-weighted-v1
Bayesian Evidence Score · measured evidence input only
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
- Observed capability
- —
- Evidence status
- No admitted measured evidence
- General preference
- —
- Coding
- —
- Agents & tools
- —
- Reasoning
- —
- Evidence breadth
- 0%
- Evidence coverage
- 0%
Market and catalogue signals · secondary, never the language Index rank
- Usage (OpenRouter popularity)
- —
- Liquidity (providers × uptime)
- —
- Open reach (HF downloads)
- —
- Surface (context / tools / modalities)
- 68.3
- Freshness
- 10.3
- · Catalogue: context 200000, reasoning, modalities Text/Image/File
- · First seen 2025-03-19
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Experimental capability estimate
Estimate policyEstimator abstained
insufficient-artifact-metadata
- Feature coverage
- 86%
- Training support
- 221 models · 129 lineages
insufficient-artifact-metadata. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Deployment readiness
Metadata index14.8
insufficient · 19% metadata coverage
- Artifact reproducibility
- 0.0
- Access & legal clarity
- 30.3
- Deployability
- 29.0
- Evaluation provenance
- 0.0
Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, a current serving provider, measured provider uptime, published provider pricing, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market activity
Venue coverage- Market Gravity
- 8.0
- OpenRouter weekly popularity
- Not listed
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
Arena preference
No matched Arena rating
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
Market Gravity breakdown
- Usage55%
- 0.0
- Liquidity25%
- 0.0
- Open reach15%
- 50.0
- Freshness5%
- 10.3
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
Specification
- Model ID
openai/o1-pro- Context window
- 200K tokens
- Declared output cap
- 100K tokens
OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
- Inputs
- Text, Image, File
- Outputs
- Text
- Tokenizer
- GPT
- Cached input tokens
- Not offered
- First seen on OpenRouter
- 19 Mar 2025
- Knowledge cutoff
- 2023-10-31
Capabilities
- Supported: Reasoning
- Not supported: Tool use
- Supported: Structured output
- Supported: Response format
- Supported: Moderated
o1-pro: common questions
How much does o1-pro cost per 1M tokens?
No live API price is listed for o1-pro in the current snapshot as of 6 November 2026 because no serving endpoint is published. ModelCap shows a price only when a provider currently lists one.
What is the context window of o1-pro?
o1-pro has a published context window of 200K tokens (200,000). The snapshot lists a 100,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Is o1-pro open-weight?
No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.
When was o1-pro released?
o1-pro first appeared in the catalogue on 19 Mar 2025, with a published knowledge cutoff of 2023-10-31. It has since been superseded by o3 Pro. Rank and price movements since then are recorded on the site's changes feed.