Sakana AI·sakana/sakana-namazu
Sakana Namazu is a language model published by Sakana AI. 1 OpenRouter endpoint is published in the current live dataset. It accepts text, image, file input and returns text. The published context limit is 262K tokens. The catalogue declares support for reasoning, tool use, structured outputs.
Providers
Uptime measured over the last 30 minutesModelCap Index · Current board
Methodology- Public rank basis
- Modeled · structural (architecture)
- Index support
- 25.0% · limited
- Index interval
- 26.7–52.0
- Rank posterior
- Not available
- Top 5 / Top 10 probability
- Not available / Not available
- Posterior as of
- Snapshot timestamp unavailable
- Evidence as of
- No admitted evaluation publication timestamp
- Identity binding
- Exact catalogue product · sakana/sakana/sakana-namazu · aggregates disclosed benchmark configurations · endpoint configuration not claimed
- Index observations used
- 0
- Qualified Index evidence point
- 52.0
- Architecture fallback
- estimated · 55% coverage · 0 anchors
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%
- Usage (OpenRouter popularity)
- 0.5
- Liquidity (providers × uptime)
- 35.3
- Open reach (HF downloads)
- —
- Surface (context / tools / modalities)
- 90.3
- Freshness
- 99.9
- · OpenRouter popularity #291
- · 1 live provider
- · Catalogue: context 262144, reasoning, tools, modalities Text/Image/File
- · First seen 2026-08-11
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 policyinsufficient-artifact-metadata
- Feature coverage
- 86%
- Training support
- 156 models · 94 lineages
insufficient-artifact-metadata. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Deployment readiness
Metadata index- Artifact reproducibility
- 0.0
- Access & legal clarity
- 30.3
- Deployability
- 80.0
- Evaluation provenance
- 0.0
Missing: artifactReproducibility.revision-sha, artifactReproducibility.architecture-and-model-type, artifactReproducibility.parameter-count, artifactReproducibility.serialized-weight-format, artifactReproducibility.base-lineage, accessLegalClarity.declared-license, accessLegalClarity.resolvable-license-terms, evaluationProvenance.admitted-evaluation-observations, evaluationProvenance.capability-family-breadth, evaluationProvenance.evaluation-source-diversity, evaluationProvenance.identity-and-source-confidence, evaluationProvenance.evaluation-dataset-revisions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market activity
Venue coverage- Market Gravity
- 21.6
- OpenRouter weekly popularity
- #291 of 299
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
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%
- 0.5
- Liquidity25%
- 35.3
- Open reach15%
- 50.0
- Freshness5%
- 99.9
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
- Context window
- 262K tokens
- Max output
- 66K tokens
- Inputs
- Text, Image, File
- Outputs
- Text
- Tokenizer
- Other
- Cached input tokens
- $0.15 / 1M
- First seen on OpenRouter
- 11 Aug 2026
Capabilities
- Supported: Reasoning
- Supported: Tool use
- Supported: Structured output
- Not supported: Response format
- Not supported: Moderated