stealthmodels.

MODEL FIELD GUIDE

Owl Alpha: Pelican

Revealed from Owl Alpha, LongCat-2.0 provides MIT-licensed MoE weights, sparse attention and a million-token context.

Drawn by this model01 / 01
Pelican benchmark result generated by this model
SVG BENCHMARKPelicanView result

A good fit for

Long-context coding and agent workflows through hosted access, or deployment on large GPU clusters.

Context window
1,000,000tokens[1]
Active parameters
48Bparameters[1]
License
MIT[1]
Model factsArchitecture, context & capabilities
Developer
Meituan[1]
Origin
China[2]
Family
LongCat[1]
Context window
1,000,000 tokens[1]
License
MIT[1]
Architecture
Mixture-of-Experts with LongCat Sparse Attention[1]
Active parameters per token
48B[1]
Input
text[1]
Output
text[1]
API access & pricingOpenRouter · $0.3 input / $1.2 output · per 1M tokens

LongCat API; input 0.3 USD/1M; cached read 0.006/1M; output 1.2/1M; Limited-time discounted USD price; list price is $0.75 input / $0.015 cached input / $2.95 output. Expiry date not stated on page.

[3]
  • OpenRouterObserved 2026-10-06
    Input $0.3Output $1.2Cached read $0.006

    per 1M tokens

    meituan/longcat-2.0[4]
  • LongCat APIObserved 2026-10-06
    Input $0.3Output $1.2Cached read $0.006

    per 1M tokens

    Available

    LongCat-2.0[3]
Run it locallyWeights, memory & deployment

rack-scale

[1] [5]
Measurements & sources5 primary references

StealthMark score

StealthMark measures fluid and visual intelligence of AI models.

General and Visual

General Intelligence

Perspective, anatomy, correct shadows, purposeful detail and physical consistency.

Visual Intelligence

Likeness, anatomy, detail, light, materials, composition and artistic expression.

Judging

Frontier Models blindly judge the AI generation unbiased through an intricate process. Our researchers control for mistakes.

Overall score

Overall combines weighted task scores on a scale from 0 to 100. Repeating a task does not increase its weight. Estimated means the total includes an estimate for one missing scene.

Benchmaxxing

Benchmaxx flags models that score unusually well on the familiar Pelican task compared with their other benchmark results. The percentage measures that imbalance, not the probability of training contamination. Flagged Pelican scores are excluded from Overall. Pelican never counts toward General or Visual.

We keep some prompts private to discourage test-specific optimization.

Scoring categories

Prompt & likeness

Subjects, actions and likeness.

Anatomy & construction

Coherent bodies, joints and machinery.

Space & placement

Perspective, scale and contact.

Light & reflections

Lighting, shadows and reflections.

Purposeful detail

Clear, purposeful small features.

Artistry & character

Composition, expression and drawing skill.

Materials & effects

Surfaces, texture and movement.

Visual integrity

Clean shapes, layers and edges.

BENCHMARK RESULTS

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StealthMark benchmark results

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