> Meta's Segment Anything Model 2.1 (Hiera-Tiny backbone) quantized to INT8 for real-time robotic segmentation. 2.0x smaller — from 298 MB to 152 MB — the smallest SAM2 variant for maximum speed on edge hardware.
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Meta's Segment Anything Model 2.1 (Hiera-Tiny backbone) quantized to INT8 for real-time robotic segmentation. 2.0x smaller — from 298 MB to 152 MB — the smallest SAM2 variant for maximum speed on edge hardware.
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2 trechos--- license: apache-2.0 base_model: facebook/sam2.1-hiera-tiny tags: - robotics - edge-deployment - anima - forge - int8 - quantized - sam2 - segmentation - image-segmentation - video-segmentation - ros2 - jetson - real-time - vision library_name: transformers pipeline_tag: image-segmentation model-index: - name: sam2.1-hiera-tiny-int8 results: - task: type: image-segmentation metrics: - name: Model Size (MB) type: model_size value: 152 - name: Compression Ratio type: compression value: 2.0 - name: Original Size (MB) type: original_size value: 298 --- # SAM 2.1 Hiera-Tiny — INT8 Quantized > Meta's Segment Anything Model 2.1 (Hiera-Tiny backbone) quantized to INT8 for real-time robotic segmentation. **2.0x smaller** — from 298 MB to 152 MB — the smallest SAM2 variant for maximum speed on edge hardware. This model is part of the **[RobotFlowLabs](https://huggingface.co/robotflowlabs)** model library, built for the **ANIMA** agentic robotics platform — a modular ROS2-native AI system that brings foundation model intelligence to real robots operating in the real world. ## Why This Model Exists When every millisecond counts — grasping a moving object, dodging an obstacle, responding to a human — you need the fastest possible segmentation. SAM2 Hiera-Tiny is the lightest SAM2 backbone, and at 152 MB after INT8 quantization, it fits comfortably alongside multiple other perception models on devices like Jetson Nano or Orin NX. ## Model Details | Property | Value | |----------|-------| | **Architecture** | Hiera-Tiny vision backbone + SAM2 decoder | | **Input Resolution** | 1024 × 1024 | | **Capabilities** | Image segmentation, video object tracking | | **Backbone Stages** | 4 stages: [1, 2, 7, 2] blocks (12 total) | | **Embed Dims** | [96, 192, 384, 768] per stage | | **Attention Heads** | [1, 2, 4, 8] per stage | | **Global Attention** | Blocks 5, 7, 9 | | **Mask Decoder** | 256-dim hidden, 8 attention heads, 3 multi-mask outputs | | **Memory Attention** | 4 layers, 2048-dim FFN, RoPE positional encoding | | **Memory Bank** | 7 frames temporal context | | **Original Model** | [`facebook/sam2.1-hiera-tiny`](https://huggingface.co/facebook/sam2.1-hiera-tiny) | | **License** | Apache-2.0 | ## Compression Results Quantized on an NVIDIA L4 24GB GPU using INT8 dynamic quantization with SafeTensors export. | Metric | Original | INT...
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