executorch-community/Qwen3-0.6B-ExecuTorch-WebGPU

Qwen3 0.6B for ExecuTorch WebGPU

This repository contains an ExecuTorch conversion of Qwen/Qwen3-0.6B for the ExecuTorch WebGPU backend, so the model runs entirely in a web browser on the visitor's GPU. It powers the corresponding demo in the ExecuTorch WebGPU Playground (launching soon on executorch.ai).

• Base model: Qwen/Qwen3-0.6B
• Format: ExecuTorch .pte programs delegated to the WebGPU backend
• Quantization: 4-bit groupwise weights (q4gsw), fp16 KV cache
• Total size: 397.1 MB

About the original model

A 0.6B-parameter dense causal language model from the Qwen3 family, with a thinking mode for multi-step reasoning and a non-thinking mode for fast chat.

• Developed by: Qwen Team, Alibaba Cloud
• Paper: Qwen3 Technical Report
• 0.6B parameters, 28 layers
• Context length 32,768 tokens
• Supports 100+ languages and dialects

For training data, evaluation results and full details, see the original model card: Qwen/Qwen3-0.6B.

Intended use and limitations

General chat, instruction following and multilingual text generation.

Small language models can state false information confidently, repeat themselves, and reflect biases in their training data. Check important outputs. See the upstream card for best-practice sampling settings.

What changed in this conversion

• Weights quantized to 4-bit groupwise (q4gsw); the KV cache is fp16
• Context capped at 8,960 tokens (upstream: 32,768)
• The playground uses non-thinking mode by default

Inputs and outputs

• forward(tokens int64 [1, 1..512], input_pos int64 [1]) -> logits float32 [1, 151936] (last position only)
• The KV cache lives inside the program; call it with up to 512 new tokens at a time, then one token per step
• Tokenize with the files in tokenizer/ (the upstream Qwen3 tokenizer) and the Qwen3 chat template

Files

File	Size	SHA-256
qwen3_0_6b_q4gsw.pte	382.0 MB	057af5734a6ce17c…
tokenizer/config.json	726 B	660db3b73d788119…
tokenizer/generation_config.json	239 B	2325da0f15bb848e…
tokenizer/merges.txt	1.6 MB	8831e4f1a0444713…
tokenizer/tokenizer.json	10.9 MB	aeb13307a71acd8f…
tokenizer/tokenizer_config.json	9.5 KB	d5d09f07b48c3086…
tokenizer/vocab.json	2.6 MB	ca10d7e9fb3ed185…

Full checksums are in manifest.json. The playground verifies them after download.

Running it

These programs were exported with the ExecuTorch WebGPU backend (backends/webgpu) and validated with the WebAssembly runtime build used by the ExecuTorch WebGPU Playground (launching soon on executorch.ai). That runtime build is not published yet; until it is, the playground is the supported way to run them. It downloads these files once, caches them in the browser, and runs everything locally.

Requirements: a browser with WebGPU enabled. The language models use the shader-f16 GPU feature when available and fall back to fp32 math without it.

Provenance

• Upstream: Qwen/Qwen3-0.6B at revision c1899de289a04d12100db370d81485cdf75e47ca (official)
• Exported with: executorch 1.5.1+cpu, torch 2.14.1+cpu, torchao 0.18.0+cpu, transformers 5.19.0 (executorch git 3b6068392324)
• Reproduce: python recipes/qwen3-0.6b.py --out out/qwen3-0.6b (recipe in export/)
• Re-running the recipe produces byte-identical files.

Citation

If you use this model, please cite the original work:

@misc{qwen3technicalreport,
  title={Qwen3 Technical Report},
  author={Qwen Team},
  year={2025},
  eprint={2505.09388},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2505.09388}
}

License

This is a derivative of the upstream model and is distributed under the same terms (apache-2.0); see LICENSE. Modifications (conversion to the ExecuTorch format and quantization) by Meta Platforms, Inc.