How does GPT-5 Pro rank among AI models?
GPT-5 Pro is a superseded version and is not on the current board as of 6 November 2026.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.
OpenAI·#115 of 504 in the all-versions archive
GPT-5 Pro is a language model from OpenAI. It ranks #115 of 504 in ModelCap's all-versions archive, with a thinly supported Index score of 64.3, partly measured on public benchmarks and partly modeled. Its score range of 58.2–70.5 spans positions #86–#152. It is listed at $15.00 per million input tokens and $120 per million output tokens from one provider. It reads up to 400K tokens of context, with no downloadable weights linked in the current source data.
Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology
ModelCap Index · All-versions archive
64.3#115
Partly measured on public benchmarks and partly modeled · range 58.2–70.5
Evidence as of 4 Nov 2026, 23:07 UTC
Superseded by GPT-5.5 Pro. It no longer holds a current-board position; its all-versions archive rank is #115.
Input
$15.00
per 1M tokens
Output
$120
per 1M tokens
Context
400K
tokens
Providers
1
endpoint
Providers
Uptime measured over the last 30 minutesOther versions (3)
ModelCap Index · All-versions archive
Methodology64.3
Partly measured on public benchmarks and partly modeled
All-versions archive
#115 of 504
Limited evidence. Measured on only 1 public benchmark, with limited support, so the score is less certain than a broadly measured one. What this label means
- Score range
- 58.2–70.5
- Rank range
- #86–#152
- Evidence as of
- 4 Nov 2026, 23:07 UTC
- Benchmarks used
- ARC-AGI-2 Verified
Technical details
- Public rank basis
- Measured · blended (measured)
- Evidence label
- Measured · blended · higher pro tier of GPT-5 (64) (93%); shrunk 0.5 toward the measured corpus
- Index support
- 2.1% · weak
- Identity binding
- Exact catalogue product · openai/openai/gpt-5-pro · aggregates disclosed benchmark configurations · endpoint configuration not claimed
- Index observations used
- 1
- Qualified Index evidence point
- 64.3
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
- 64.3 ± 4.8
- Independent share
- 3%
- Shrink toward corpus
- -0.5
- 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
- 28.7
- Evidence status
- provisional · 2% mass
- General preference
- —
- Coding
- —
- Agents & tools
- —
- Reasoning
- 28.7
- Evidence breadth
- 3%
- Evidence coverage
- 2%
Market and catalogue signals · secondary, never the language Index rank
- Usage (OpenRouter popularity)
- 0.8
- Liquidity (providers × uptime)
- 95.8
- Open reach (HF downloads)
- —
- Surface (context / tools / modalities)
- 93.3
- Freshness
- 22.1
- · OpenRouter popularity #323
- · 1 live provider
- · Catalogue: context 400000, reasoning, tools, modalities Image/Text/File
- · First seen 2025-10-06
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
BES evidence selected · measured input only
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.
Deployment readiness
Metadata index31.6
limited · 50% metadata coverage
- Artifact reproducibility
- 0.0
- Access & legal clarity
- 30.3
- Deployability
- 60.0
- Evaluation provenance
- 37.9
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, measured provider uptime, 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
- 33.0
- OpenRouter weekly popularity
- #323 of 339
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%
- 0.8
- Liquidity25%
- 95.8
- Open reach15%
- 50.0
- Freshness5%
- 22.1
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/gpt-5-pro- Context window
- 400K tokens
- Declared output cap
- 128K 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
- Image, Text, File
- Outputs
- Text
- Tokenizer
- GPT
- Cached input tokens
- Not offered
- First seen on OpenRouter
- 6 Oct 2025
- Knowledge cutoff
- 2024-09-30
Capabilities
- Supported: Reasoning
- Supported: Tool use
- Supported: Structured output
- Supported: Response format
- Supported: Moderated
Benchmark leaderboards featuring GPT-5 Pro
All leaderboardsGPT-5 Pro: common questions
How much does GPT-5 Pro cost per 1M tokens?
GPT-5 Pro is listed at $15.00 per 1M input tokens and $120 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $90.00 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of GPT-5 Pro?
GPT-5 Pro has a published context window of 400K tokens (400,000). The snapshot lists a 128,000 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 GPT-5 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.
Which API providers serve GPT-5 Pro?
One provider serves GPT-5 Pro through OpenRouter as of 6 November 2026: OpenAI. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has GPT-5 Pro been evaluated on?
GPT-5 Pro has published results on 1 public board tracked by ModelCap as of 6 November 2026: ARC-AGI-2 18.3% (#149 of 280). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
When was GPT-5 Pro released?
GPT-5 Pro first appeared in the catalogue on 6 Oct 2025, with a published knowledge cutoff of 2024-09-30. It has since been superseded by GPT-5.5 Pro. Rank and price movements since then are recorded on the site's changes feed.