Raon 1 mini preview is a language model from KRAFTON. It ranks #66 of 351 on ModelCap's current board, with an Index score of 62.1, modeled from the publisher's launch results against measured models. Its score range of 53.5–70.6 spans positions #41–#99. Its weights are openly downloadable.
Modeled from the publisher's launch results against measured models
Current board
#66 of 351
Score range
53.5–70.6
Rank range
#41–#99
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · global-corpus-prior over 211 held-out anchors (8%); launch card against 2 resolved peers on 12 rows (92%); exceeds every named peer on 2 of 12 rows; optimism haircut 0.4 from cross-lab-probe; shrunk 1 toward the measured corpus
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
62.1 ± 6.7
Independent share
0%
Shrink toward corpus
-1.0
Peer ceiling share
17%
Optimism haircut
−0.4 points · cross lab probe, 6 probes
Method
precision-weighted-v1
Channels fused into this model’s launch placement
Channel
Estimate
Share
Publisher corpus prior · not independent
global-corpus-prior over 211 held-out anchors
51.3 ± 23.3
8%
Launch card against resolved peers · not independent
launch card against 2 resolved peers on 12 rows
63.0 ± 7.0
92%
· Launch card row aa-lcr: inside the resolved peer range
· Launch card row aime-2026: inside the resolved peer range
· Launch card row automationbench: claims below every resolved peer
· Launch card row bfcl-v-4-overall: claims below every resolved peer
· Launch card row gdpval: claims above every resolved peer
· Launch card row gpqa-diamond: inside the resolved peer range
· Launch card row hmmt-2026: inside the resolved peer range
· Launch card row ifbench: claims above every resolved peer
· Launch card row livecodebench-v-6: inside the resolved peer range
· Launch card row mmlu-pro: claims below every resolved peer
· Launch card row scicode: claims below every resolved peer
· Launch card row terminal-bench-lite: claims below every resolved peer
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)
51.6
Surface (context / tools / modalities)
0.0
Freshness
98.1
· HF 30d downloads 1177
· Catalogue surface
· First seen 2026-10-21
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.
Not yet published: the base model it derives from, a current serving provider, measured provider uptime, published provider pricing, declared context and output limits, 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 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
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%
51.6
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
98.1
Time since first public availability, on a six-month half-life.
Specification
Model ID
KRAFTON/Raon-1-mini-preview
Declared output cap
Unknown
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
Outputs
Text
Cached input tokens
Not offered
First seen on OpenRouter
21 Oct 2026
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.
How does Raon 1 mini preview rank among AI models?
Raon 1 mini preview holds ModelCap Index position #66 of 351 ranked language models as of 25 October 2026, with an Index score of 62.1 (interval 53.5–70.6); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
How much does Raon 1 mini preview cost per 1M tokens?
No live API price is listed for Raon 1 mini preview in the current snapshot as of 25 October 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.
Is Raon 1 mini preview 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 KRAFTON/Raon-1-mini-preview on Hugging Face.
Which benchmarks has Raon 1 mini preview been evaluated on?
Raon 1 mini preview's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 25 October 2026. The evidence panel names each source and its publication date.
When was Raon 1 mini preview released?
Raon 1 mini preview first appeared in the catalogue on 21 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.