MA
ENT-00000895 · AI Model

Mamba

Mamba is a AI model associated with Mamba, classified in LXKeys.world as Foundation / Language Model.

Level V PersistentActiveDocumented
Human record

Overview

Mamba is documented as a foundation model or model-family record associated with Mamba. Its relevance comes from selective state-space sequence model architecture used as an alternative to attention-based transformers. The entity is useful for tracing model lineage, provider strategy, capability evolution and relationships between assistants, APIs and downstream products.

Timeline

  1. 2023Initial model publication or release

    Mamba entered the documented public record in 2023. This event is retained at the precision supported by the Entry’s reviewed source history.

Capabilities

Language or multimodal model capabilityAPI or deployment integrationReasoning, generation or representation learningModel-family relationship mapping

Known limitations

Capabilities vary by release, deployment setting and evaluation method.Operational details may differ across hosted APIs, open releases or downstream integrations.
Technical and structured detail

Technical description

Structured LXKeys.world registry record for Mamba. Entity type: AI Model; classification: Foundation / Language Model; creator/organization context: Carnegie Mellon University / Princeton University. Canonical source anchor: https://github.com/state-spaces/mamba. The record tracks source authority, first public appearance, timeline, capabilities, limitations, registry status and graph relationships. Automatic refresh is limited to sources explicitly classified as OFFICIAL and enabled for updates; documentary and research references remain non-authoritative unless reviewed.

Controlled tags

MambaFoundation ModelDocumented AIstate-space
Relationship graph

Mamba

Open in full graph
Mamba
Creator or DeveloperOutgoing
Carnegie Mellon University / Princeton University

Carnegie Mellon University / Princeton University is identified as a creator, developer or originating actor for Mamba.

Registry CategoryOutgoing
Foundation Models

Model-level entity connected to the foundation-model layer of the registry.

Associated OrganizationIncoming
Mamba-2

Mamba is the organization or ecosystem associated with Mamba-2.

Machine readable layer

Structured entry data for human tools, AI systems and machine clients.

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    ],
    "@type": "Thing",
    "identifier": "ENT-00000895",
    "name": "Mamba",
    "alternateName": [],
    "additionalType": {
        "category": "Models",
        "type": "AI Model",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "Mamba is a AI model associated with Mamba, classified in LXKeys.world as Foundation / Language Model.",
    "creator": "Carnegie Mellon University / Princeton University",
    "url": "https://lxkeys.world/entry.php?id=ENT-00000895&lang=en",
    "sameAs": "https://github.com/state-spaces/mamba",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00000895",
        "kind": "Models",
        "type": "AI Model",
        "subtype": "",
        "classification": "Foundation / Language Model",
        "organization": "Mamba",
        "originContext": "Research model",
        "firstPublicAppearance": "2023",
        "currentStatus": "Active",
        "documentationStatus": "Documented",
        "documentationIndex": {
            "total": 82,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 19,
            "level": "Level V Persistent"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:02+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:02+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "facts": [],
        "capabilities": [
            "Language or multimodal model capability",
            "API or deployment integration",
            "Reasoning, generation or representation learning",
            "Model-family relationship mapping"
        ],
        "limitations": [
            "Capabilities vary by release, deployment setting and evaluation method.",
            "Operational details may differ across hosted APIs, open releases or downstream integrations."
        ],
        "tags": [
            "Mamba",
            "Foundation Model",
            "Documented AI",
            "state-space"
        ],
        "timeline": [
            {
                "date": "2023",
                "title": "Initial model publication or release",
                "description": "Mamba entered the documented public record in 2023. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://github.com/state-spaces/mamba",
                "verification_status": "source_backed_curated_baseline"
            }
        ],
        "relationships": [
            {
                "target": "Carnegie Mellon University / Princeton University",
                "type": "Creator or Developer",
                "description": "Carnegie Mellon University / Princeton University is identified as a creator, developer or originating actor for Mamba.",
                "evidence_level": "documentary"
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            {
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                "type": "Registry Category",
                "description": "Model-level entity connected to the foundation-model layer of the registry.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Mamba official reference",
                "url": "https://github.com/state-spaces/mamba",
                "source_type": "Official Documentation",
                "verification_status": "verified",
                "authority": "TRUSTED_PRIMARY",
                "role": "code_repository",
                "update_enabled": false,
                "authority_basis": "curated-corpus-refresh-2026-09-08"
            }
        ],
        "canonical": [],
        "imageMeta": []
    }
}
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