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torch / matmul3b6488

torch_matmul_3b6488 · FlashInfer-Bench baselines · python · Apache-2.0

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Vendorable · source mirrored · Apache-2.0View source →

No package. Vendor the mirrored source: 7 lines, Apache-2.0, pinned at da91508.

main.py
curl "https://kernelindex.com/api/v1/implementations/flashinfer-torch-matmul-3b6488?include=source"
interfacepython
revisionda915083d4c7
symbolrun
pathmain.py
Compatibility
measured onNVIDIA B200
declared hardwareCPU, NVIDIA A100, NVIDIA H100
architecturessm_90, unknown
dtypesfp16

Benchmark evidence

43 measurements across 1 GPU, fastest first.

Operation / workload
Hardware
Latency
Rank
Observed
GEMM n6144 k4096fp16 · [24, 4096]
NVIDIA B200
18.5µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [7, 4096]
NVIDIA B200
18.5µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [2, 4096]
NVIDIA B200
18.5µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [1, 4096]
NVIDIA B200
18.6µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [56, 4096]
NVIDIA B200
18.9µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [4, 4096]
NVIDIA B200
19.0µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [48, 4096]
NVIDIA B200
19.0µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [8, 4096]
NVIDIA B200
19.0µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [35, 4096]
NVIDIA B200
19.1µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [40, 4096]
NVIDIA B200
19.1µs
#2 of 6
2025-10-16
Show all 43 measurements ›
GEMM n6144 k4096fp16 · [15, 4096]
NVIDIA B200
19.1µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [128, 4096]
NVIDIA B200
19.2µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [120, 4096]
NVIDIA B200
19.2µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [112, 4096]
NVIDIA B200
19.2µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [64, 4096]
NVIDIA B200
19.3µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [104, 4096]
NVIDIA B200
19.6µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [16, 4096]
NVIDIA B200
19.7µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [32, 4096]
NVIDIA B200
19.8µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [96, 4096]
NVIDIA B200
19.9µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [88, 4096]
NVIDIA B200
20.0µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [72, 4096]
NVIDIA B200
20.4µs
#2 of 5
2025-10-16
GEMM n6144 k4096fp16 · [70, 4096]
NVIDIA B200
20.4µs
#1 of 5
2025-10-16
GEMM n6144 k4096fp16 · [80, 4096]
NVIDIA B200
20.6µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [160, 4096]
NVIDIA B200
21.1µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [152, 4096]
NVIDIA B200
21.2µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [248, 4096]
NVIDIA B200
21.9µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [256, 4096]
NVIDIA B200
22.1µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [224, 4096]
NVIDIA B200
22.3µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [240, 4096]
NVIDIA B200
22.3µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [232, 4096]
NVIDIA B200
22.5µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [136, 4096]
NVIDIA B200
22.6µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [208, 4096]
NVIDIA B200
22.9µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [184, 4096]
NVIDIA B200
23.0µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [176, 4096]
NVIDIA B200
23.1µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [144, 4096]
NVIDIA B200
23.2µs
#2 of 5
2025-10-16
GEMM n6144 k4096fp16 · [192, 4096]
NVIDIA B200
23.2µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [168, 4096]
NVIDIA B200
24.0µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [216, 4096]
NVIDIA B200
24.4µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [200, 4096]
NVIDIA B200
24.6µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [972, 4096]
NVIDIA B200
41.2µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [2053, 4096]
NVIDIA B200
75.9µs
#2 of 6
2025-10-16
GEMM n6144 k4096fp16 · [2379, 4096]
NVIDIA B200
84.1µs
#1 of 6
2025-10-16
GEMM n6144 k4096fp16 · [8192, 4096]
NVIDIA B200
298.2µs
#2 of 6
2025-10-16

Reported · How evidence levels are derived →

Source and license

sourcehttps://huggingface.co/datasets/flashinfer-ai/flashinfer-trace
commitda915083d4c7c5e61aa3005e3d17ae488e0fc71c
revision digestsha256:646dfd9659e29864030afefca67c9a88b9dc860258de81be0d4cbfe4260d9d84
license declaredApache-2.0
license concludedApache-2.0
authorsbaseline
imported2026-08-16

Kernel source

main.py7 lines
import torch
import torch.nn.functional as F

def run(A: torch.Tensor, B: torch.Tensor):
    C = F.linear(A, B)
    return C

Source code from FlashInfer-Bench (flashinfer-ai/flashinfer-trace) · Apache-2.0

Best evidence level for this revision: reported

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