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torch_matmul_655587

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-655587?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 n28672 k4096fp16 · [8, 4096]
NVIDIA B200
55.4µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [7, 4096]
NVIDIA B200
55.4µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [2, 4096]
NVIDIA B200
55.5µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [1, 4096]
NVIDIA B200
55.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [4, 4096]
NVIDIA B200
55.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [24, 4096]
NVIDIA B200
55.7µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [15, 4096]
NVIDIA B200
55.7µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [16, 4096]
NVIDIA B200
55.8µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [32, 4096]
NVIDIA B200
56.3µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [35, 4096]
NVIDIA B200
56.5µs
#1 of 8
2025-10-16
Show all 43 measurements ›
GEMM n28672 k4096fp16 · [48, 4096]
NVIDIA B200
56.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [40, 4096]
NVIDIA B200
56.8µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [64, 4096]
NVIDIA B200
56.9µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [70, 4096]
NVIDIA B200
57.2µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [80, 4096]
NVIDIA B200
57.3µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [56, 4096]
NVIDIA B200
57.4µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [72, 4096]
NVIDIA B200
57.5µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [144, 4096]
NVIDIA B200
58.2µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [160, 4096]
NVIDIA B200
58.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [136, 4096]
NVIDIA B200
58.9µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [96, 4096]
NVIDIA B200
61.8µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [112, 4096]
NVIDIA B200
61.8µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [128, 4096]
NVIDIA B200
61.9µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [88, 4096]
NVIDIA B200
62.5µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [104, 4096]
NVIDIA B200
62.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [120, 4096]
NVIDIA B200
62.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [176, 4096]
NVIDIA B200
63.1µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [168, 4096]
NVIDIA B200
63.8µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [152, 4096]
NVIDIA B200
64.7µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [192, 4096]
NVIDIA B200
65.0µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [224, 4096]
NVIDIA B200
65.0µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [184, 4096]
NVIDIA B200
65.1µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [240, 4096]
NVIDIA B200
65.1µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [256, 4096]
NVIDIA B200
65.3µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [208, 4096]
NVIDIA B200
66.1µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [200, 4096]
NVIDIA B200
66.2µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [232, 4096]
NVIDIA B200
66.3µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [248, 4096]
NVIDIA B200
66.3µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [216, 4096]
NVIDIA B200
66.6µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [972, 4096]
NVIDIA B200
182.4µs
#2 of 8
2025-10-16
GEMM n28672 k4096fp16 · [2053, 4096]
NVIDIA B200
358.4µs
#1 of 8
2025-10-16
GEMM n28672 k4096fp16 · [2379, 4096]
NVIDIA B200
439.8µs
#2 of 8
2025-10-16
GEMM n28672 k4096fp16 · [8192, 4096]
NVIDIA B200
1.36ms
#1 of 8
2025-10-16

Reported · How evidence levels are derived →

Source and license

sourcehttps://huggingface.co/datasets/flashinfer-ai/flashinfer-trace
commitda915083d4c7c5e61aa3005e3d17ae488e0fc71c
revision digestsha256:da5fc07d5dc5dd69e2a4d51b89909d7f2ffb92a6d8fa4a5df5592d188d79221d
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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