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ModelCap

Ornith 1.5 397B

Official publisher releaseOpen weights

Ornith Ai·#21 of 280 on the current board

Ornith 1.5 397B is a language model from Ornith Ai. It ranks #21 of 280 on ModelCap's current board, with an Index score of 76.5, modeled from the publisher's launch results against measured models. Its score range of 67.2–85.7 spans positions #3–#42. Its weights are openly downloadable.

Figures as of 4 Oct 2026, 03:19 UTC · download the public dataset · methodology

ModelCap Index · Current board
76.5#21
Modeled from the publisher's launch results against measured models · range 67.2–85.7
Market Gravity
17.9
Secondary market signal

OpenRouter endpoint status could not be refreshed. This model is not treated as currently served until a successful observation arrives.

Input
Self-hosted
weights only · no listed API price
Output
Self-hosted
weights only · no listed API price
Context
—
tokens
Providers
0
endpoints

Providers

Uptime measured over the last 30 minutes

Current provider status is unavailable.

Reported evaluation leads (11)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.

Dataset / taskMetricValueRevisionProvenance
cais/hle
hle
—44.6
Unpinned
not published
Reported
Not used in launch estimate
cais/hle
hle
—56.1
Unpinned
not published
Reported
Not used in launch estimate
claw-eval/Claw-Eval
general
—81.4
Unpinned
not published
Reported
Not used in launch estimate
datacurve/deep-swe
deep_swe
—56
Unpinned
not published
Reported
Used in launch estimate
harborframework/terminal-bench-2.1
terminalbench_2_1
—86.1
Unpinned
not published
Reported
Used in launch estimate
harborframework/terminal-bench-2.1
terminalbench_2_1
—85.2
Unpinned
not published
Reported
Used in launch estimate
hkust-nlp/Toolathlon
toolathlon_verified
—71.2
Unpinned
not published
Reported
Not used in launch estimate
Idavidrein/gpqa
diamond
—92.8
Unpinned
not published
Reported
Not used in launch estimate
ScaleAI/SWE-bench_Pro
SWE_Bench_Pro
—65.1
Unpinned
not published
Reported
Used in launch estimate
SWE-bench/SWE-bench_Multilingual
swe_bench_multilingual_%_resolved
—79.6
Unpinned
not published
Reported
Used in launch estimate
SWE-bench/SWE-bench_Verified
swe_bench_%_resolved
—86
Unpinned
not published
Reported
Used in launch estimate

Other versions (1)

ModelCap Index · Current board

Methodology
76.5
Modeled from the publisher's launch results against measured models
Current board
#21 of 280
Score range
67.2–85.7
Rank range
#3–#42
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · global-corpus-prior over 231 held-out anchors (10%); launch card against 2 resolved peers on 11 rows (90%); exceeds every named peer on 3 of 11 rows; optimism haircut 0 from cross-lab-probe; shrunk 2.3 toward the measured corpus
Index support
40.0% · limited
Identity binding
Exact catalogue product · ornith-ai/ornith-ai/Ornith-1.5-397B · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata ornith-ai/Ornith-1.5-397B@8f6cc8a7aea505364523f84ccf37706e8aea0ee7 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
76.5
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
76.5 ± 7.2
Independent share
0%
Shrink toward corpus
-2.3
Peer ceiling share
27%
Optimism haircut
None required · cross lab probe, 7 probes
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
global-corpus-prior over 231 held-out anchors
55.6 ± 22.810%
Launch card against resolved peers · not independent
launch card against 2 resolved peers on 11 rows
78.8 ± 7.690%
  • · Launch card row deepswe: inside the resolved peer range
  • · Launch card row gpqa-diamond: inside the resolved peer range
  • · Launch card row hle-with-tools: inside the resolved peer range
  • · Launch card row hle-without-tools: inside the resolved peer range
  • · Launch card row mcp-atlas: inside the resolved peer range
  • · Launch card row nl-2-repo: inside the resolved peer range
  • · Launch card row swe-bench-multilingual: claims above every resolved peer
  • · Launch card row swe-bench-pro: inside the resolved peer range
  • · Launch card row swe-bench-verified: claims above every resolved peer
  • · Launch card row terminal-bench-2-1: claims above every resolved peer
  • · Launch card row toolathlon-verified: inside the resolved peer range
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)
91.4
Surface (context / tools / modalities)
0.0
Freshness
83.7
  • · HF 30d downloads 350632
  • · Catalogue surface
  • · First seen 2026-08-18

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 policy
35.4
19.1–51.8 uncertainty interval
Excluded from rank
Confidence
71%
Training support
241 models · 138 lineages
Out-of-domain check
in domain
Feature coverage
71%
Lineage-held-out error
9.0 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
47.9
partial · 52% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
8.0
Evaluation provenance
0.0

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 activity

Venue coverage
Market Gravity
17.9
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

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%
91.4

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
83.7

Time since first public availability, on a six-month half-life.

Specification

Model ID
ornith-ai/Ornith-1.5-397B
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
18 Aug 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.

Access
Open weights
Licence
mit
Pinned revision
8f6cc8a7aea5
Parameters
403.4B
Architecture
Qwen3_5MoeForConditionalGeneration
Model type
qwen3_5_moe
Hugging Face downloads (30d)
351K
Downloads (all time)
726K
Likes
91
Repository updated
23 Aug 2026, 06:21 UTC

Alternatives to Ornith 1.5 397B, by the numbers

Ranked neighbours

Models within 3 places of #21 on the ModelCap Index.

Other ranked Ornith Ai models

The same publisher's other current models with a public Index position.

Ornith 1.5 397B: common questions

How does Ornith 1.5 397B rank among AI models?

Ornith 1.5 397B holds ModelCap Index position #21 of 280 ranked language models as of 4 October 2026, with an Index score of 76.5 (interval 67.2–85.7); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Ornith 1.5 397B cost per 1M tokens?

No live API price is listed for Ornith 1.5 397B in the current snapshot as of 4 October 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.

Is Ornith 1.5 397B open-weight?

Open weights (mit). 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 ornith-ai/Ornith-1.5-397B on Hugging Face.

Which benchmarks has Ornith 1.5 397B been evaluated on?

Ornith 1.5 397B'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 4 October 2026. The evidence panel names each source and its publication date.

When was Ornith 1.5 397B released?

Ornith 1.5 397B first appeared in the catalogue on 18 Aug 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.