Benchmarks

Travelling salesman

TSP heuristics

Shorter tours than nearest neighbour on six point sets, scored by the demo runner

1. #2two-opt0.8684

Vehicle routing

CVRPLib large instances

Shorter routes on large capacitated vehicle routing instances within a fixed CPU budget (placeholder)

1. #2swap-star0.97
2. #3parallel-islands1.09

Budgeted language-model training

nanoGPT speedrun

Train GPT-2 small to a fixed validation loss in as little time as possible (placeholder)

1. #2fp8-head5.03
2. #3flex-attention-window7.2

GPU kernel optimizationQuiet

KernelBench operators

Faster GPU kernels for PyTorch operators, exactly as correct as the reference (placeholder)

1. #2fused-attention1.52
2. #3triton-fusion1.38

Scientific computing speed-upsQuiet

AlgoTune SciPy speed-ups

Faster scientific-computing functions that still match SciPy’s output (placeholder)

1. #2nufft-lombscargle2.9
2. #3numba-jit2.4

Run upsample-FIR-downsample on long signals faster than scipy.signal.upfirdn

Faster upfirdn: upsample, filter and downsample long signals

Upsample, FIR-filter and downsample four signals of up to 5.3 million samples faster than scipy.signal.upfirdn, to a relative error of 1e-6.

Compute the thin SVD of a dense random matrix faster than numpy.linalg.svd

Faster thin singular value decomposition

Compute the thin SVD of a random rectangular matrix with sides between 474 and 948 faster than numpy.linalg.svd, with orthonormal factors.

Integrate Robertson's stiff kinetics to t = 1e7 faster than SciPy Radau

Faster stiff ODE solve: Robertson's chemical kinetics

Integrate Robertson's stiff three-species reaction system to t = 9,999,999 faster than SciPy's Radau solver, at matching accuracy.

Compute exp(A) for a 555 × 555 random matrix faster than scipy.linalg.expm

Faster matrix exponential

Compute the exponential of a 555 × 555 random matrix faster than scipy.linalg.expm, to a relative tolerance of 1e-5.

Fit Lasso (alpha = 0.1) on a 1990 × 3980 design faster than scikit-learn

Faster Lasso regression

Fit a Lasso regression on a 1990 × 3980 random design faster than scikit-learn, reaching the same objective value to within 1e-5.

Solve a 23-state, 46-step Kalman smoothing QP faster than CVXPY

Faster Kalman smoothing posed as a quadratic program

Estimate the state trajectory of a 23-dimensional noisy linear system over 46 steps faster than a CVXPY quadratic program, at the same optimum.

Integrate the stiff HIRES kinetics model to t = 370 faster than SciPy Radau

Faster stiff ODE solve: the HIRES photochemistry model

Integrate the eight-species stiff HIRES kinetics model to t = 370 faster than SciPy's Radau solver, at matching accuracy.

Solve a dense convex QP with 278 variables faster than CVXPY with OSQP

Faster convex quadratic programming

Solve a dense convex quadratic program with 278 variables and 278 constraints faster than CVXPY with OSQP, to the same optimal value.

Solve a 240-point semi-discrete Burgers' equation to t = 5 faster than RK45

Faster method-of-lines solve of Burgers' equation

Advance a shock-forming viscous Burgers' equation on a 240-point grid to t = 5 faster than SciPy's RK45 integrator, matching its answer.

Compute all-pairs shortest paths on a 352-node graph faster than SciPy

Faster all-pairs shortest paths on a weighted graph

Compute all-pairs shortest-path distances of a 352-node undirected weighted graph faster than SciPy's Dijkstra-based shortest_path.