microsoft/onnxruntime plugin-ep-webgpu/v0.3.0

ONNX Runtime WebGPU Plugin EP v0.3.0

on GitHub

ONNX Runtime WebGPU Plugin EP 0.3.0 expands model and data-type coverage, improves generative-model performance, and strengthens configuration, reliability, and release tooling.

These release notes were drafted with AI assistance.

Highlights

Model and operator coverage

• Added initial PagedAttention support, MRotaryEmbedding, GRU, DFT, PRelu, HardSwish, Trilu, Max and Min, and MatMulBnb4. (#31611, #31976, #29840, #29454, #30512, #29828, #29845, #29833, #29587)
• Expanded integer support across common operators, including int64 for Add, Cast, Clip, Concat, Equal, Gather, Min, Max, ReduceSum, Reshape, Sub, Tile, and Where; uint8 for Cast, Expand, Gather, and Reshape; and int32/uint32 for CumSum and Tile. (#28804, #29392, #29830, #29834, #29839, #29844, #29847, #29854, #29861, #29897, #31049, #31702, #31709, #31714)
• Added 2-bit GatherBlockQuantized support and integrated ONNX 1.22 with opset 27. (#29054, #28754)

Generative models

• Added quantized KV cache support and expanded GQA with sliding-window cache, batched right-padded prompts, and FlashAttention graph capture for Gemma 4. (#28059, #29236, #29247, #29904)
• Fixed GQA and quantized KV cache correctness for rotary batched prefill, split-reduce decode, and per-batch sequence lengths. (#29002, #29593, #29752)

Performance

• Added deferred dispatch to parallelize shader compilation during cold start. (#29557)
• Added Intel subgroup-matrix MatMul and FP16 Gemm kernels, then extended them with batched-B and odd-N weight support and additional tiling optimizations. (#29271, #29592, #29749, #29813, #29893, #30514)
• Switched Softmax and non-flash Attention to an online softmax algorithm and tuned FlashAttention decode. (#29694, #29724, #29586)

Reliability and configuration

• Added a robustness provider option, made the pending-dispatch limit configurable, and exposed WebGPU buffer-cache options through the JavaScript API. (#31971, #28894, #29017)
• Improved validation and bounds handling in GridSample, LSTM, DynamicQuantizedLSTM, Slice, and GatherBlockQuantized, and fixed WebGPU data-transfer callbacks on Windows x86. (#28704, #29030, #29255, #29595, #31568)
• Corrected profiling timestamp alignment with the ONNX Runtime profiler. (#29021)

Build and release tooling

• Added device-free compile-only sessions for offline graph transformation and removed the dynamic Duktape/Node WGSL-generation path in favor of generated shader sources. (#29681, #28355, #29141)
• Upgraded Dawn, fixed parallel-build races, refreshed release and packaging documentation, and enabled WebGPU CI on plugin release branches. (#29389, #29040, #29777, #29059, #32090)

Contributors

Thank you to everyone who contributed to this release:

@AngelGalindo7, @daijh, @danielsongmicrosoft, @edgchen1, @fanchenkong1, @feich-ms, @guschmue, @haoxli, @hariharans29, @Honry, @huningxin, @jchen10, @Jiawei-Shao, @miaobin, @mingmingtasd, @mirounga, @mustjab, @nicholascelestin, @prathikr, @qjia7, @Reranko05, @Shivani767, @skottmckay, @ssam18, @sushraja-msft, @tairenpiao, @tianleiwu, @titaiwangms, @wuisabel-gif, @xhcao, and @xiaofeihan1.

Scope: commits affecting ONNX Runtime WebGPU Plugin EP code, tests, build integration, and packaging since plugin-ep-webgpu/v0.2.1.