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Model predictive control test set (sparse)

Number of problems 4
Benchmark version 2.7.0
Date 2026-07-23 10:04:16.763457+00:00
CPU AMD Ryzen 7 8845HS w/ Radeon 780M Graphics
Run by @stephane-caron
Results file mpc_qpbenchmark_sparse.parquet
Results checksum sha256:e58f0e5bc6be0cd24b3041c5f3e0333da6abeaa98d5418a440daac34307696d1

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Contents

Description

Problems arising from model predictive control in robotics, restricted to instances with sparse cost matrices (QUADCMPC).

Solvers

solver version
clarabel 0.11.1
cvxopt 1.3.3
gurobi 13.0.2 (size-limited)
highs 1.15.1
kvxopt 1.3.3.1
osqp 1.1.3
piqp 0.6.3
proxqp 0.7.3
qpalm 1.2.6
scs 3.2.11
sip 0.0.2

All solvers were called via qpsolvers v4.13.0.

Results by settings

Default settings

Solvers are compared over the whole test set by shifted geometric mean (shm). Lower is better, 1.0 is the best.

Success rate (%) Runtime (shm) Primal residual (shm) Dual residual (shm) Duality gap (shm)
clarabel 100.0 1.7 1.0 1.0 1.0
cvxopt 0.0 3207.3 1.0 1.0 1.0
gurobi 0.0 3207.3 1.0 1.0 1.0
highs 50.0 1338.1 1.0 1.0 1.0
kvxopt 0.0 3207.3 1.0 1.0 1.0
osqp 100.0 1.1 1.0 1.0 1.0
piqp 100.0 26.6 1.0 1.0 1.0
proxqp 100.0 17.4 1.0 1.0 1.0
qpalm 100.0 1.0 1.0 1.0 1.0
scs 100.0 7.6 1.0 1.0 1.0
sip 100.0 2.2 1.0 1.0 1.0

High accuracy settings

Solvers are compared over the whole test set by shifted geometric mean (shm). Lower is better, 1.0 is the best.

Success rate (%) Runtime (shm) Primal residual (shm) Dual residual (shm) Duality gap (shm)
clarabel 100.0 1.0 1.0 1.0 1.0
cvxopt 0.0 1714.6 1.0 1.0 1.0
gurobi 0.0 1714.6 1.0 1.0 1.0
highs 0.0 715.4 1.0 1248.4 476930.8
kvxopt 0.0 1714.6 1.0 1.0 1.0
osqp 0.0 1714.6 1.0 1.0 1.0
piqp 100.0 14.2 1.0 1.0 1.0
proxqp 50.0 712.0 1.0 1.0 1.0
qpalm 100.0 1.8 1.0 1.0 1.0
scs 100.0 17.9 1.0 1.0 1.0
sip 100.0 1.2 1.0 1.0 1.0

Low accuracy settings

Solvers are compared over the whole test set by shifted geometric mean (shm). Lower is better, 1.0 is the best.

Success rate (%) Runtime (shm) Primal residual (shm) Dual residual (shm) Duality gap (shm)
clarabel 100.0 1.2 1.0 1.0 1.0
cvxopt 0.0 3025.4 1.0 1.0 1.0
gurobi 0.0 3025.4 1.0 1.0 1.0
highs 0.0 3.4 1.0 1.0 322.2
kvxopt 0.0 3025.4 1.0 1.0 1.0
osqp 100.0 1.4 1.0 1.0 1.0
piqp 100.0 14.6 1.0 1.0 1.0
proxqp 100.0 17.2 1.0 1.0 1.0
qpalm 75.0 1.0 1.0 1.0 1.3
scs 100.0 1.5 1.0 1.0 1.0
sip 100.0 1.0 1.0 1.0 1.0

Mid accuracy settings

Solvers are compared over the whole test set by shifted geometric mean (shm). Lower is better, 1.0 is the best.

Success rate (%) Runtime (shm) Primal residual (shm) Dual residual (shm) Duality gap (shm)
clarabel 100.0 1.1 1.0 1.0 1.0
cvxopt 0.0 2383.8 1.0 1.0 1.0
gurobi 0.0 2383.8 1.0 1.0 1.0
highs 0.0 994.2 1.0 1.7 479.4
kvxopt 0.0 2383.8 1.0 1.0 1.0
osqp 25.0 1625.8 1.0 1.0 1.0
piqp 100.0 16.3 1.0 1.0 1.0
proxqp 75.0 459.5 1.0 1.0 1.0
qpalm 100.0 1.0 1.0 1.0 1.0
scs 100.0 9.1 1.0 1.0 1.0
sip 100.0 1.1 1.0 1.0 1.0

Results by metric

Success rate

Precentage of problems each solver is able to solve:

default high_accuracy low_accuracy mid_accuracy
clarabel 100 100 100 100
cvxopt 0 0 0 0
gurobi 0 0 0 0
highs 50 0 0 0
kvxopt 0 0 0 0
osqp 100 0 100 25
piqp 100 100 100 100
proxqp 100 50 100 75
qpalm 100 100 75 100
scs 100 100 100 100
sip 100 100 100 100

Rows are solvers and columns are settings. We consider that a solver successfully solved a problem when (1) it returned with a success status and (2) its solution satisfies optimality conditions within tolerance. The second table below summarizes the frequency at which solvers return success (1) and the corresponding solution did indeed pass tolerance checks.

Percentage of problems where "solved" return codes are correct:

default high_accuracy low_accuracy mid_accuracy
clarabel 100 100 100 100
cvxopt 100 100 100 100
gurobi 100 100 100 100
highs 100 50 0 50
kvxopt 100 100 100 100
osqp 100 100 100 100
piqp 100 100 100 100
proxqp 100 100 100 100
qpalm 100 100 75 100
scs 100 100 100 100
sip 100 100 100 100

Computation time

We compare solver computation times over the whole test set using the shifted geometric mean. Intuitively, a solver with a shifted-geometric-mean runtime of Y is Y times slower than the best solver over the test set. See Metrics for details.

Shifted geometric mean of solver computation times (1.0 is the best):

default high_accuracy low_accuracy mid_accuracy
clarabel 1.7 1.0 1.2 1.1
cvxopt 3207.3 1714.6 3025.4 2383.8
gurobi 3207.3 1714.6 3025.4 2383.8
highs 1338.1 715.4 3.4 994.2
kvxopt 3207.3 1714.6 3025.4 2383.8
osqp 1.1 1714.6 1.4 1625.8
piqp 26.6 14.2 14.6 16.3
proxqp 17.4 712.0 17.2 459.5
qpalm 1.0 1.8 1.0 1.0
scs 7.6 17.9 1.5 9.1
sip 2.2 1.2 1.0 1.1

Rows are solvers and columns are solver settings. The shift is sh = 10. As in the OSQP and ProxQP benchmarks, we assume a solver's run time is at the time limit when it fails to solve a problem.

Optimality conditions

Primal residual

The primal residual measures the maximum (equality and inequality) constraint violation in the solution returned by a solver. We use the shifted geometric mean to compare solver primal residuals over the whole test set. Intuitively, a solver with a shifted-geometric-mean primal residual of Y is Y times less precise on constraints than the best solver over the test set. See Metrics for details.

Shifted geometric means of primal residuals (1.0 is the best):

default high_accuracy low_accuracy mid_accuracy
clarabel 1.0 1.0 1.0 1.0
cvxopt 1.0 1.0 1.0 1.0
gurobi 1.0 1.0 1.0 1.0
highs 1.0 1.0 1.0 1.0
kvxopt 1.0 1.0 1.0 1.0
osqp 1.0 1.0 1.0 1.0
piqp 1.0 1.0 1.0 1.0
proxqp 1.0 1.0 1.0 1.0
qpalm 1.0 1.0 1.0 1.0
scs 1.0 1.0 1.0 1.0
sip 1.0 1.0 1.0 1.0

Rows are solvers and columns are solver settings. The shift is sh = 10. A solver that fails to find a solution receives a primal residual equal to the full primal tolerance.

Dual residual

The dual residual measures the maximum violation of the dual feasibility condition in the solution returned by a solver. We use the shifted geometric mean to compare solver dual residuals over the whole test set. Intuitively, a solver with a shifted-geometric-mean dual residual of Y is Y times less precise on the dual feasibility condition than the best solver over the test set. See Metrics for details.

Shifted geometric means of dual residuals (1.0 is the best):

default high_accuracy low_accuracy mid_accuracy
clarabel 1.0 1.0 1.0 1.0
cvxopt 1.0 1.0 1.0 1.0
gurobi 1.0 1.0 1.0 1.0
highs 1.0 1248.4 1.0 1.7
kvxopt 1.0 1.0 1.0 1.0
osqp 1.0 1.0 1.0 1.0
piqp 1.0 1.0 1.0 1.0
proxqp 1.0 1.0 1.0 1.0
qpalm 1.0 1.0 1.0 1.0
scs 1.0 1.0 1.0 1.0
sip 1.0 1.0 1.0 1.0

Rows are solvers and columns are solver settings. The shift is sh = 10. A solver that fails to find a solution receives a dual residual equal to the full dual tolerance.

Duality gap

The duality gap measures the consistency of the primal and dual solutions returned by a solver. A duality gap close to zero ensures that the complementarity slackness optimality condition is satisfied. We use the shifted geometric mean to compare solver duality gaps over the whole test set. Intuitively, a solver with a shifted-geometric-mean duality gap of Y is Y times less precise on the complementarity slackness condition than the best solver over the test set. See Metrics for details.

Shifted geometric means of duality gaps (1.0 is the best):

default high_accuracy low_accuracy mid_accuracy
clarabel 1.0 1.0 1.0 1.0
cvxopt 1.0 1.0 1.0 1.0
gurobi 1.0 1.0 1.0 1.0
highs 1.0 476930.8 322.2 479.4
kvxopt 1.0 1.0 1.0 1.0
osqp 1.0 1.0 1.0 1.0
piqp 1.0 1.0 1.0 1.0
proxqp 1.0 1.0 1.0 1.0
qpalm 1.0 1.0 1.3 1.0
scs 1.0 1.0 1.0 1.0
sip 1.0 1.0 1.0 1.0

Rows are solvers and columns are solver settings. The shift is sh = 10. A solver that fails to find a solution receives a duality gap equal to the full gap tolerance.

Settings

There are 4 settings: default, high_accuracy, low_accuracy and mid_accuracy. They validate solutions using the following tolerances:

tolerance default high_accuracy low_accuracy mid_accuracy
dual 1 1e-09 0.001 1e-06
gap 1 1e-09 0.001 1e-06
primal 1 1e-09 0.001 1e-06
runtime 10 10 10 10

Solvers for each settings are configured as follows:

solver parameter default high_accuracy low_accuracy mid_accuracy
clarabel tol_feas - 1e-09 0.001 1e-06
clarabel tol_gap_abs - 1e-09 0.001 1e-06
clarabel tol_gap_rel - 0 0 0
cvxopt feastol - 1e-09 0.001 1e-06
gurobi FeasibilityTol - 1e-09 0.001 1e-06
gurobi OptimalityTol - 1e-09 0.001 1e-06
gurobi TimeLimit 10.0 10 10 10
highs dual_feasibility_tolerance - 1e-09 0.001 1e-06
highs primal_feasibility_tolerance - 1e-09 0.001 1e-06
highs time_limit 10.0 10 10 10
kvxopt feastol - 1e-09 0.001 1e-06
osqp eps_abs - 1e-09 0.001 1e-06
osqp eps_rel - 0 0 0
osqp time_limit 10.0 10 10 10
piqp check_duality_gap - 1 1 1
piqp eps_abs - 1e-09 0.001 1e-06
piqp eps_duality_gap_abs - 1e-09 0.001 1e-06
piqp eps_duality_gap_rel - 0 0 0
piqp eps_rel - 0 0 0
proxqp check_duality_gap - 1 1 1
proxqp eps_abs - 1e-09 0.001 1e-06
proxqp eps_duality_gap_abs - 1e-09 0.001 1e-06
proxqp eps_duality_gap_rel - 0 0 0
proxqp eps_rel - 0 0 0
qpalm eps_abs - 1e-09 0.001 1e-06
qpalm eps_rel - 0 0 0
qpalm time_limit 10.0 10 10 10
scs eps_abs - 1e-09 0.001 1e-06
scs eps_rel - 0 0 0
scs time_limit_secs 10.0 10 10 10
sip eps_abs - 1e-09 0.001 1e-06
sip eps_rel - 0 0 0
sip time_limit 10.0 10 10 10

Known limitations

The following issues have been identified as impacting the fairness of this benchmark. Keep them in mind when drawing conclusions from the results.

  • #60: Conversion to SOCP limits performance of ECOS
  • #88: CPU thermal throttling

CPU info

Property Value
arch X86_64
arch_string_raw x86_64
bits 64
brand_raw AMD Ryzen 7 8845HS w/ Radeon 780M Graphics
count 16
family 25
flags 3dnowext, 3dnowprefetch, abm, adx, aes, amd_lbr_v2, aperfmperf, apic, arat, avx, avx2, avx512_bf16, avx512_bitalg, avx512_vbmi2, avx512_vnni, avx512_vpopcntdq, avx512bitalg, avx512bw, avx512cd, avx512dq, avx512f, avx512ifma, avx512vbmi, avx512vbmi2, avx512vl, avx512vnni, avx512vpopcntdq, bmi1, bmi2, bpext, cat_l3, cdp_l3, clflush, clflushopt, clwb, clzero, cmov, cmp_legacy, constant_tsc, cpb, cppc, cpuid, cpuid_fault, cqm, cqm_llc, cqm_mbm_local, cqm_mbm_total, cqm_occup_llc, cr8_legacy, cx16, cx8, dbx, de, decodeassists, erms, extapic, extd_apicid, f16c, flush_l1d, flushbyasid, fma, fpu, fsgsbase, fsrm, fxsr, fxsr_opt, gfni, ht, hw_pstate, ibpb, ibrs, ibrs_enhanced, ibs, invpcid, irperf, lahf_lm, lbrv, lm, mba, mca, mce, misalignsse, mmx, mmxext, monitor, movbe, msr, mtrr, mwaitx, nonstop_tsc, nopl, npt, nrip_save, nx, ospke, osvw, osxsave, overflow_recov, pae, pat, pausefilter, pci_l2i, pclmulqdq, pdpe1gb, perfctr_core, perfctr_llc, perfctr_nb, perfmon_v2, pfthreshold, pge, pku, pni, popcnt, pqe, pqm, pse, pse36, rapl, rdpid, rdpru, rdrand, rdrnd, rdseed, rdt_a, rdtscp, rep_good, sep, sha, sha_ni, skinit, smap, smca, smep, ssbd, sse, sse2, sse4_1, sse4_2, sse4a, ssse3, stibp, succor, svm, svm_lock, syscall, tce, topoext, tsc, tsc_scale, umip, user_shstk, v_spec_ctrl, vaes, vgif, vmcb_clean, vme, vmmcall, vnmi, vpclmulqdq, wbnoinvd, wdt, x2apic, x2avic, xgetbv1, xsave, xsavec, xsaveerptr, xsaveopt, xsaves, xtopology
l1_data_cache_size 262144
l1_instruction_cache_size 262144
l2_cache_associativity 6
l2_cache_line_size 1024
l2_cache_size 8388608
l3_cache_size 1048576
model 117
python_version 3.14.6.final.0 (64 bit)
stepping 2
vendor_id_raw AuthenticAMD