Download build/webgpu/bench.json from webgpu-kernels/com.microsoft.LinearAttention: direct link, hf CLI and curl.
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https://huggingface.co/kernels/webgpu-kernels/com.microsoft.LinearAttention/resolve/v1/build/webgpu/bench.json
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hf download hf://webgpu-kernels/com.microsoft.LinearAttention@v1/build/webgpu/bench.json
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curl -L -o bench.json https://huggingface.co/kernels/webgpu-kernels/com.microsoft.LinearAttention/resolve/v1/build/webgpu/bench.json
44.2 kB
| { | |
| "tunableSpace": { | |
| "dvGroups": [2, 4, 8], | |
| "tileV": [4, 8, 16], | |
| "gatedTileV": [2, 4, 8], | |
| "chunkSize": [16, 32], | |
| "chunkTileV": [16, 32] | |
| }, | |
| "cases": [ | |
| { | |
| "name": "linear-attention-f32-zero-32x4x16x16", | |
| "preset": "smoke", | |
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| "valueT": { "shape": [1, 32, 32], "dtype": "float32", "dist": "normal", "seed": 203, "scale": 0.2 } | |
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| "outputs": { | |
| "outputT": { "shape": [1, 32, 64], "dtype": "float32" }, | |
| "presentStateT": { "shape": [1, 2, 16, 16], "dtype": "float32" } | |
| }, | |
| "bench": { | |
| "primary": true, | |
| "metrics": [ | |
| { "type": "gflops", "value": "2 * args.batch * args.seq * (args.qHeads + args.kvHeads) * args.dk * args.dv" } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-f32-state-32x4x16x16", | |
| "preset": "smoke", | |
| "vars": { "batch": 1, "seq": 32, "qHeads": 4, "kvHeads": 2, "dk": 16, "dv": 16 }, | |
| "attrs": { "q_num_heads": 4, "kv_num_heads": 2, "update_rule": "gated_delta", "scale": 0.25 }, | |
| "inputs": { | |
| "queryT": { "shape": [1, 32, 64], "dtype": "float32", "dist": "normal", "seed": 202, "scale": 0.2 }, | |
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| "pastStateT": { "shape": [1, 2, 16, 16], "dtype": "float32", "dist": "normal", "seed": 205, "scale": 0.1 }, | |
| "decayT": { "shape": [1, 32, 32], "dtype": "float32", "dist": "normal", "seed": 206, "scale": 0.1 }, | |
| "betaT": { "shape": [1, 32, 2], "dtype": "float32", "dist": "normal", "seed": 207, "scale": 0.1 } | |
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| "outputT": { "shape": [1, 32, 64], "dtype": "float32" }, | |
| "presentStateT": { "shape": [1, 2, 16, 16], "dtype": "float32" } | |
| }, | |
| "bench": { | |
| "primary": true, | |
| "metrics": [ | |
| { | |
| "type": "gflops", | |
| "value": "2 * args.batch * args.seq * (args.qHeads + 2 * args.kvHeads) * args.dk * args.dv" | |
| } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-f32-linear-state-32x4x16x16", | |
| "preset": "smoke", | |
| "vars": { "batch": 1, "seq": 32, "qHeads": 4, "kvHeads": 2, "dk": 16, "dv": 16 }, | |
| "attrs": { "q_num_heads": 4, "kv_num_heads": 2, "update_rule": "linear", "scale": 0.25 }, | |
| "inputs": { | |
| "queryT": { "shape": [1, 32, 64], "dtype": "float32", "dist": "normal", "seed": 208, "scale": 0.2 }, | |
| "keyT": { "shape": [1, 32, 32], "dtype": "float32", "dist": "normal", "seed": 209, "scale": 0.2 }, | |
| "valueT": { "shape": [1, 32, 32], "dtype": "float32", "dist": "normal", "seed": 210, "scale": 0.2 }, | |
| "pastStateT": { "shape": [1, 2, 16, 16], "dtype": "float32", "dist": "normal", "seed": 211, "scale": 0.1 } | |
| }, | |
| "outputs": { | |
| "outputT": { "shape": [1, 32, 64], "dtype": "float32" }, | |
| "presentStateT": { "shape": [1, 2, 16, 16], "dtype": "float32" } | |
| }, | |
| "bench": { | |
| "metrics": [ | |
| { "type": "gflops", "value": "2 * args.batch * args.seq * (args.qHeads + args.kvHeads) * args.dk * args.dv" } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-linear-state-scalar-f16-seq1536-pathology", | |
| "preset": "stress", | |
| "provenance": { | |
| "source": "synthetic benchmark", | |
| "notes": "Long-sequence supplied-state case at head_dim_k 16. It exercises the recurrent small-dk route's serial token recurrence and distinguishes it from the chunked prefill decomposition." | |
| }, | |
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| "keyT": { "shape": [4, 1536, 32], "dtype": "float16", "dist": "normal", "seed": 315, "scale": 0.2 }, | |
| "valueT": { "shape": [4, 1536, 32], "dtype": "float16", "dist": "normal", "seed": 316, "scale": 0.2 }, | |
| "pastStateT": { "shape": [4, 2, 16, 16], "dtype": "float16", "dist": "normal", "seed": 317, "scale": 0.1 } | |
| }, | |
| "outputs": { | |
| "outputT": { "shape": [4, 1536, 64], "dtype": "float16" }, | |
| "presentStateT": { "shape": [4, 2, 16, 16], "dtype": "float16" } | |
| }, | |
| "bench": { | |
| "primary": true, | |
| "metrics": [ | |
| { "type": "gflops", "value": "2 * args.batch * args.seq * (args.qHeads + args.kvHeads) * args.dk * args.dv" } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-gated_delta-scalar-headdimk6-seq1536-stress", | |
| "preset": "stress", | |
| "vars": { "batch": 8, "seq": 1536, "qHeads": 4, "kvHeads": 4, "dk": 6, "dv": 12 }, | |
| "attrs": { "q_num_heads": 4, "kv_num_heads": 4, "update_rule": "gated_delta", "scale": 0.25 }, | |
| "inputs": { | |
| "queryT": { "shape": [8, 1536, 24], "dtype": "float32", "dist": "normal", "seed": 301, "scale": 0.2 }, | |
| "keyT": { "shape": [8, 1536, 24], "dtype": "float32", "dist": "normal", "seed": 302, "scale": 0.2 }, | |
| "valueT": { "shape": [8, 1536, 48], "dtype": "float32", "dist": "normal", "seed": 303, "scale": 0.2 }, | |
| "pastStateT": { "shape": [8, 4, 6, 12], "dtype": "float32", "dist": "normal", "seed": 304, "scale": 0.1 }, | |
| "decayT": { "shape": [8, 1536, 4], "dtype": "float32", "dist": "normal", "seed": 305, "scale": 0.1 }, | |
| "betaT": { "shape": [8, 1536, 4], "dtype": "float32", "dist": "normal", "seed": 306, "scale": 0.1 } | |
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| "outputs": { | |
| "outputT": { "shape": [8, 1536, 48], "dtype": "float32" }, | |
| "presentStateT": { "shape": [8, 4, 6, 12], "dtype": "float32" } | |
| }, | |
| "bench": { | |
| "primary": true, | |
| "metrics": [ | |
| { | |
| "type": "gflops", | |
| "value": "2 * args.batch * args.seq * (args.qHeads + 2 * args.kvHeads) * args.dk * args.dv" | |
| } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-linear-scalar-f16-seq1536-stress", | |
| "preset": "stress", | |
| "vars": { "batch": 4, "seq": 1536, "qHeads": 4, "kvHeads": 2, "dk": 16, "dv": 16 }, | |
| "attrs": { "q_num_heads": 4, "kv_num_heads": 2, "update_rule": "linear", "scale": 0.25 }, | |
| "inputs": { | |
| "queryT": { "shape": [4, 1536, 64], "dtype": "float16", "dist": "normal", "seed": 311, "scale": 0.2 }, | |
| "keyT": { "shape": [4, 1536, 32], "dtype": "float16", "dist": "normal", "seed": 312, "scale": 0.2 }, | |
| "valueT": { "shape": [4, 1536, 32], "dtype": "float16", "dist": "normal", "seed": 313, "scale": 0.2 } | |
| }, | |
| "outputs": { | |
| "outputT": { "shape": [4, 1536, 64], "dtype": "float16" }, | |
| "presentStateT": { "shape": [4, 2, 16, 16], "dtype": "float16" } | |
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| "bench": { | |
| "primary": true, | |
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| { "type": "gflops", "value": "2 * args.batch * args.seq * (args.qHeads + args.kvHeads) * args.dk * args.dv" } | |
| ] | |
| }, | |
| "provenance": { | |
| "source": "synthetic benchmark", | |
| "notes": "A long-sequence scalar recurrence uses the zero-state branch with no entry state." | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-gated-delta-f32-bonsai-m16-h48-kv16-dk128-dv128", | |
| "preset": "stress", | |
| "vars": { "batch": 1, "seq": 16, "qHeads": 48, "kvHeads": 16, "dk": 128, "dv": 128 }, | |
| "attrs": { "q_num_heads": 48, "kv_num_heads": 16, "update_rule": "gated_delta", "scale": 0.08838834764831845 }, | |
| "inputs": { | |
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| "valueT": { "shape": [1, 16, 2048], "dtype": "float32", "dist": "normal", "seed": 322, "scale": 0.05 }, | |
| "pastStateT": { "shape": [1, 16, 128, 128], "dtype": "float32", "dist": "normal", "seed": 323, "scale": 0.02 }, | |
| "decayT": { "shape": [1, 16, 16], "dtype": "float32", "dist": "normal", "seed": 324, "scale": 0.08 }, | |
| "betaT": { "shape": [1, 16, 16], "dtype": "float32", "dist": "normal", "seed": 325, "scale": 0.08 } | |
| }, | |
| "outputs": { | |
| "outputT": { "shape": [1, 16, 6144], "dtype": "float32", "dist": "empty" }, | |
| "presentStateT": { "shape": [1, 16, 128, 128], "dtype": "float32", "dist": "empty" } | |
| }, | |
| "bench": { | |
| "primary": true, | |
| "metrics": [ | |
| { | |
| "type": "gflops", | |
| "value": "2 * args.batch * args.seq * (args.qHeads + 2 * args.kvHeads) * args.dk * args.dv" | |
| } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-gated-delta-f16-bonsai-m16-h48-kv16-dk128-dv128", | |
| "preset": "stress", | |
| "vars": { "batch": 1, "seq": 16, "qHeads": 48, "kvHeads": 16, "dk": 128, "dv": 128 }, | |
| "attrs": { "q_num_heads": 48, "kv_num_heads": 16, "update_rule": "gated_delta", "scale": 0.08838834764831845 }, | |
| "inputs": { | |
| "queryT": { "shape": [1, 16, 6144], "dtype": "float16", "dist": "normal", "seed": 326, "scale": 0.05 }, | |
| "keyT": { "shape": [1, 16, 2048], "dtype": "float16", "dist": "normal", "seed": 327, "scale": 0.05 }, | |
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| "decayT": { "shape": [1, 16, 16], "dtype": "float16", "dist": "normal", "seed": 330, "scale": 0.08 }, | |
| "betaT": { "shape": [1, 16, 16], "dtype": "float16", "dist": "normal", "seed": 331, "scale": 0.08 } | |
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| "outputT": { "shape": [1, 16, 6144], "dtype": "float16", "dist": "empty" }, | |
| "presentStateT": { "shape": [1, 16, 128, 128], "dtype": "float16", "dist": "empty" } | |
| }, | |
| "bench": { | |
| "primary": true, | |
| "metrics": [ | |
| { | |
| "type": "gflops", | |
| "value": "2 * args.batch * args.seq * (args.qHeads + 2 * args.kvHeads) * args.dk * args.dv" | |
| } | |
| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-qwen3next-decode-s1", | |
| "preset": "model", | |
| "provenance": { | |
| "notes": "Qwen3-Next class defaults (linear_num_value_heads 32, linear_num_key_heads 16, linear_key_head_dim 128, linear_value_head_dim 128) at a decode step, where the recurrence carries the whole cost. Float uniforms use scale/offset: log-decay spans log(0.9) to 0, beta spans 0.1 to 0.9, and keys are bounded by 1/sqrt(dk) so squared key norms do not exceed one." | |
| }, | |
| "vars": { "batch": 1, "seq": 1, "qHeads": 32, "kvHeads": 16, "dk": 128, "dv": 128 }, | |
| "attrs": { | |
| "q_num_heads": 32, | |
| "kv_num_heads": 16, | |
| "update_rule": "gated_delta", | |
| "scale": 0.08838834764831843, | |
| "chunk_size": 64 | |
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| "queryT": { "shape": [1, 1, 4096], "dtype": "float32", "dist": "normal", "seed": 8100, "scale": 0.3 }, | |
| "keyT": { | |
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| "valueT": { "shape": [1, 1, 2048], "dtype": "float32", "dist": "normal", "seed": 8102, "scale": 0.3 }, | |
| "pastStateT": { "shape": [1, 16, 128, 128], "dtype": "float32", "dist": "normal", "seed": 8103, "scale": 0.1 }, | |
| "decayT": { | |
| "shape": [1, 1, 2048], | |
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| "signed": false, | |
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| "signed": false, | |
| "offset": 0.1, | |
| "scale": 0.8 | |
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| "outputs": { | |
| "outputT": { "shape": [1, 1, 4096], "dtype": "float32" }, | |
| "presentStateT": { "shape": [1, 16, 128, 128], "dtype": "float32" } | |
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| "bench": { | |
| "metrics": [ | |
| { | |
| "type": "gflops", | |
| "value": "2 * args.batch * args.seq * (args.qHeads + 2 * args.kvHeads) * args.dk * args.dv" | |
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| ] | |
| } | |
| }, | |
| { | |
| "name": "linear-attention-qwen3next-prefill-s512", | |
| "preset": "model", | |
| "provenance": { | |
| "notes": "Qwen3-Next class defaults over a 512-token prefill chunk. Float uniforms use scale/offset: log-decay spans log(0.9) to 0, beta spans 0.1 to 0.9, and keys are bounded by 1/sqrt(dk) so squared key norms do not exceed one." | |
| }, | |
| "vars": { "batch": 1, "seq": 512, "qHeads": 32, "kvHeads": 16, "dk": 128, "dv": 128 }, | |
| "attrs": { | |
| "q_num_heads": 32, | |
| "kv_num_heads": 16, | |
| "update_rule": "gated_delta", | |
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| "keyT": { | |
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| "valueT": { "shape": [1, 512, 2048], "dtype": "float32", "dist": "normal", "seed": 8202, "scale": 0.3 }, | |
| "pastStateT": { "shape": [1, 16, 128, 128], "dtype": "float32", "dist": "normal", "seed": 8203, "scale": 0.1 }, | |
| "decayT": { | |
| "shape": [1, 512, 2048], | |
| "dtype": "float32", | |
| "dist": "uniform", | |
| "seed": 8204, | |
| "signed": false, | |
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| "seed": 8205, | |
| "signed": false, | |
| "offset": 0.1, | |
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| "outputs": { | |
| "outputT": { "shape": [1, 512, 4096], "dtype": "float32" }, | |
| "presentStateT": { "shape": [1, 16, 128, 128], "dtype": "float32" } | |
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| "bench": { | |
| "metrics": [ | |
| { | |
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| }, | |
| { | |
| "name": "linear-attention-qwen3next-prefill-s2048", | |
| "preset": "model", | |
| "provenance": { | |
| "notes": "Qwen3-Next class defaults over a 2048-token prefill chunk, eight chunk_size 64 blocks per workgroup pass. Float uniforms use scale/offset: log-decay spans log(0.9) to 0, beta spans 0.1 to 0.9, and keys are bounded by 1/sqrt(dk) so squared key norms do not exceed one." | |
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| "vars": { "batch": 1, "seq": 2048, "qHeads": 32, "kvHeads": 16, "dk": 128, "dv": 128 }, | |
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| "kv_num_heads": 16, | |
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| "scale": 0.08838834764831843, | |
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| "dist": "uniform", | |
| "seed": 8304, | |
| "signed": false, | |
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| "shape": [1, 2048, 16], | |
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| "dist": "uniform", | |
| "seed": 8305, | |
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| "outputs": { | |
| "outputT": { "shape": [1, 2048, 4096], "dtype": "float32" }, | |
| "presentStateT": { "shape": [1, 16, 128, 128], "dtype": "float32" } | |
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| "bench": { | |
| "metrics": [ | |
| { | |
| "type": "gflops", | |
| "value": "2 * args.batch * args.seq * (args.qHeads + 2 * args.kvHeads) * args.dk * args.dv" | |
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| } | |
| }, | |
| { | |
| "name": "bench-linear_geometry_float32_float32_g0_zero", | |
| "provenance": { | |
| "notes": "Small-head linear recurrence with shared keys, standard or inverse query grouping, odd value dimensions, independent state dtype, and retained or empty-sequence state windows." | |
| }, | |
| "attrs": { "q_num_heads": 4, "kv_num_heads": 2, "update_rule": "linear", "state_window": 3, "scale": 0.375 }, | |
| "inputs": { | |
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| "keyT": { | |
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| "shape": [2, 33, 8], | |
| "data": { "kind": "fillFloat32", "sinStep": 0.23, "cosStep": 0.31, "scale": 0.05 } | |
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| "valueT": { | |
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| "outputT": { "dtype": "float32", "shape": [2, 33, 28] }, | |
| "presentStateT": { "dtype": "float32", "shape": [3, 2, 2, 8, 7] } | |
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