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    Runs as a custom pluginSegmentationRecommendedVerified 2026-11-05

    SAM 2.1 Hiera Tiny (small, base-plus)

    facebook/sam2.1-hiera-tiny

    SAM 2.1 Hiera Tiny (small, base-plus) is a image and video segmentation model (Apache-2.0). Can run on Mixpeek as a custom plugin.

    Mixpeek does not run it today. It can run as a custom plugin: the weights load without remote code.

    No demo for SAM 2.1 Hiera Tiny (small, base-plus) yet

    A video, image, slideshow or playground goes here once we record one on our own data.

    What it is good and bad at

    Best at
    Fast promptable masks; the size to try on CPU for image masks from detector boxes.
    Worst at
    Lower mask quality than Large on fine boundaries; video tracking is slow on CPU.
    Task
    Segmentation
    Input
    Image, Video
    Output
    Masks, Scores, Tracks
    Use cases
    Segmentation, Object detection, Tracking
    Why we recommend it
    Apache-2.0 promptable masks small enough to try on CPU. Not yet evaluated by Mixpeek.

    Templates that use it

    No template uses this model yet. Browse templates.

    Input and output

    Input

    image
    resolution
    1024x1024 (longest side resized)
    video
    frames
    streamed frame by frame with a memory bank
    prompts
    points (positive/negative), boxes, or a mask; no text

    Output

    masks
    binary masks per prompt (3 candidates with IoU scores for ambiguous prompts)
    scores
    predicted IoU
    tracks
    object ids across video frames

    How Mixpeek wires it

    Extractors
    None today
    Feature URIs
    None today
    Vector indexes
    None
    Retriever stages
    None
    Combines with
    • detector boxes (RT-DETR, D-FINE) -> SAM 2 box prompts -> masks -> masked crops -> SigLIP vectors
    • masks per frame -> tracks -> object documents spanning a time range

    How it runs

    Status
    Runs as a custom plugin Not served. Would run as a custom extractor plugin with transformers Sam2Model (safetensors, no remote code), prompted by boxes from a permissive detector.
    Serve apps
    None
    Runtime
    transformers Sam2Model + Sam2Processor (Sam2VideoModel for video)
    Weights
    safetensors, no remote code
    Parameters
    39 M
    Size on disk
    156 MB
    Preprocessing
    Resize longest side to 1024, pad, normalize ImageNet mean/std; prompts rescaled to the same frame.
    Postprocessing
    Upsample low-res mask logits, threshold at 0, pick the best mask by predicted IoU.
    Serving
    both
    Hardware
    Runs on CPU (slower without a GPU)

    Scale to zero

    Minimum replicas
    0
    Maximum replicas
    1
    Idle timeout
    600 s
    Memory
    2 GB
    CPUs
    2
    GPUs
    0
    Cold start, node warm
    Not recorded
    Cold start, new node
    Not recorded

    Measured cost

    Unmeasured

    No committed measurement; plan row 3 measures it in the standalone image.

    Our evaluations

    Unmeasured

    We have not evaluated this model on our own data yet. Publisher results are in the sources below.

    Questions

    What is SAM 2.1 Hiera Tiny (small, base-plus) best at?
    Fast promptable masks; the size to try on CPU for image masks from detector boxes.
    What are the limits of SAM 2.1 Hiera Tiny (small, base-plus)?
    Lower mask quality than Large on fine boundaries; video tracking is slow on CPU.
    Can SAM 2.1 Hiera Tiny (small, base-plus) be used commercially?
    Yes. Apache-2.0 weights and code; no use restrictions.
    How does SAM 2.1 Hiera Tiny (small, base-plus) run on Mixpeek?
    Not served. Would run as a custom extractor plugin with transformers Sam2Model (safetensors, no remote code), prompted by boxes from a permissive detector.