Runs in the browser · Vision
Run SAM 2.1 Hiera Tiny in your browser
SAM 2.1 Hiera Tiny downloads 32.1 MB over WebGPU (q4f16), or 59.1 MB over WebAssembly (uint8), to cut a precise mask around an object you point at entirely in the tab with Transformers.js. No install, no server.
Vision · onnx-community/sam2.1-hiera-tiny-ONNX
- Parameters
- 38.96M
- Pipeline task
- custom
Reading
Same as SlimSAM: transformers.js has no mask-generation pipeline() task. SAM 2 is a distinct architecture from SAM 1, so it uses the Sam2Model and Sam2Processor classes (not SamModel/SamProcessor) with a point or box prompt.
0.82 MB/M params against a 1.73 MB/M vision median: light for its parameter count.
The quant ladder spans 4.6x: 32.1 MB (q4f16) to 148.4 MB (fp32).
Will it run in your browser?
Checking for WebGPU support…
All measured variants
| Variant | Size |
|---|---|
| q4f16 WebGPU pick | 32.1 MB |
| bnb4 | 47.3 MB |
| q4 | 49.1 MB |
| uint8 WASM pick | 59.1 MB |
| fp16 | 74.4 MB |
| q8 | 118.2 MB |
| fp32 | 148.4 MB |
Sizes measured from the HuggingFace API file tree for onnx-community/sam2.1-hiera-tiny-ONNX, not estimated.
Use it with Transformers.js
import { Sam2Model, Sam2Processor, RawImage } from "@huggingface/transformers";
const model = await Sam2Model.from_pretrained("onnx-community/sam2.1-hiera-tiny-ONNX", {
device: "webgpu",
dtype: "q4f16", // use "uint8" for the WASM build
});
const processor = await Sam2Processor.from_pretrained("onnx-community/sam2.1-hiera-tiny-ONNX");
const image = await RawImage.read("https://your-image-url.jpg");
const input_points = [[[340, 250]]]; // one (x, y) click point on the object to mask
const inputs = await processor(image, { input_points });
const outputs = await model(inputs);
const masks = await processor.post_process_masks(
outputs.pred_masks,
inputs.original_sizes,
inputs.reshaped_input_sizes,
);
Requires npm install @huggingface/transformers (or the CDN build). This model needs the lower-level API shown above, not pipeline() (see the Reading panel above).
Embed this
[](https://localmodel.run/browser/sam2.1-hiera-tiny) <a href="https://localmodel.run/browser/sam2.1-hiera-tiny"><img src="https://localmodel.run/badge/browser/sam2.1-hiera-tiny/size.svg" alt="SAM 2.1 Hiera Tiny in browser" /></a> Sources
Same job, different size
FAQ
WebGPU or WASM for SAM 2.1 Hiera Tiny, in practice?
Chrome, Edge, and Safari 26+ run the WebGPU build (q4f16) on the GPU. Firefox has WebGPU on Windows and Apple Silicon Macs but not everywhere yet. Any browser without a WebGPU adapter falls back automatically to the WebAssembly build (uint8) on CPU: same model, slower to load, slower to run.
What does q4f16 mean for SAM 2.1 Hiera Tiny?
The WebGPU build here uses q4f16: 4-bit weights with some layers kept at 16-bit for stability: WebGPU's usual smallest clean build. The WASM fallback uses uint8: 8-bit integers: about a quarter the size of fp32, with a smaller quality trade than 4-bit.
Sizes measured 2026-08-01 from the HuggingFace API. Last validated 2026-09-14. See all browser models or the methodology.