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
25.9
Evidence status
confirmed · 74% mass
General preference
25.6
Coding
27.8
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
53%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
—
Liquidity (providers × uptime)
—
Open reach (HF downloads)
76.4
Surface (context / tools / modalities)
0.0
Freshness
31.2
· HF 30d downloads 9894
· Catalogue surface
· First seen 2025-11-19
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.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
OpenRouter weekly popularity across the full model catalogue.
Liquidity25%
0.0
Independent providers versus the model's open or closed cohort, weighted by uptime.
Open reach15%
76.4
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
31.2
Time since first public availability, on a six-month half-life.
Specification
Context window
— tokens
Max output
—
Inputs
Text
Outputs
Text
Tokenizer
—
Cached input tokens
Not offered
First seen on OpenRouter
19 Nov 2025
Capabilities
Not supported: Reasoning
Not supported: Tool use
Not supported: Structured output
Not supported: Response format
Not supported: Moderated
Weights & access
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
Olmo 3 32B Think is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
How much does Olmo 3 32B Think cost per 1M tokens?
No live API price is listed for Olmo 3 32B Think in the current snapshot as of 22 September 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.
Is Olmo 3 32B Think open-weight?
Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is allenai/Olmo-3-32B-Think on Hugging Face.
Which benchmarks has Olmo 3 32B Think been evaluated on?
Olmo 3 32B Think has published results on 1 public board tracked by ModelCap as of 22 September 2026: Arena coding 1364 (#239 of 397). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
When was Olmo 3 32B Think released?
Olmo 3 32B Think first appeared in the catalogue on 19 Nov 2025. It has since been superseded by Olmo 3.1 32B Think. Rank and price movements since then are recorded on the site's changes feed.