Conjectures.io

Entry #131

Completed
Hotkey
5Gjrxj…nbr8Ru
Sent
13 Nov 2026, 02:42 UTC
Source
5d59118caa9e

Progress

  1. Queued
  2. Proof
  3. Planned
  4. Timing
  5. Done

Done means every board has a decision. It does not mean the entry took a board over.

On each board

BoardRunsTimeDecision
Overallvs #61Done2 of 2 runs0.942×Generated 0.936×, real models 0.948×Not significantGain lower bound -0.3%Guard passed
MLPvs #44Done2 of 2 runs1.032×Generated 1.029×, real models 1.035×Above the barGain lower bound -36.6%Guard passed
ResNetvs #59Done2 of 2 runs0.961×Generated 0.971×, real models 0.952×Not significantGain lower bound -0.9%Guard passed
MobileNetvs #53Done2 of 2 runs1.065×Generated 1.181×, real models 0.960×Above the barGain lower bound -20.7%Guard passed
Normalized MLPvs #48Done2 of 2 runs1.014×Generated 0.978×, real models 1.051×Above the barGain lower bound -32.9%Guard passed
Mixervs #58Done2 of 2 runs1.104×Generated 1.061×, real models 1.150×Above the barGain lower bound -38.9%Guard passed
Recurrentvs #62Done2 of 2 runs0.993×Generated 1.031×, real models 0.956×Above the barGain lower bound -3.7%Guard passed

The source stays private while it holds a board, and for entries that never held one.

Every run

Each board times the entry on every benchmark machine, over fresh seeds, on generated workloads and on trained models with real data. A run's time combines the two suites by their published weights; the bars below split it by model, batch and input, and by real model.

Overall2 runs

RunsGenerated 0.936× · real models 0.948×

MachineTime
  1. prod-amd64Seed 31540951950.938×Done1 attempt0.008× of the baseline kernels' time
  2. prod-arm64Seed 31540951950.946×Done1 attempt0.010× of the baseline kernels' time

By model and inputGuard at 1.100×

MLP

  • Batch 1, normal1.060×
  • Batch 1, sparse0.991×
  • Batch 1, wide1.162×

Mixer

  • Batch 1, normal1.006×
  • Batch 1, sparse1.078×
  • Batch 1, wide1.027×

ResNet

  • Batch 1, normal0.972×
  • Batch 1, sparse0.891×
  • Batch 1, wide0.946×

MobileNet

  • Batch 1, normal0.913×
  • Batch 1, sparse0.928×
  • Batch 1, wide0.913×

Recurrent

  • Batch 1, normal0.852×
  • Batch 1, sparse0.846×
  • Batch 1, wide0.833×

Normalized MLP

  • Batch 1, normal0.893×
  • Batch 1, sparse0.938×
  • Batch 1, wide0.984×

Real models

  • appliance-energy-mixer on Appliance Energy Prediction1.408×
  • compact-mixer on digits1.200×
  • compact-mixer on fashion0.991×
  • compact-mixer on mnist1.022×
  • compact-mlp on digits1.022×
  • compact-mlp on fashion0.771×
  • compact-mlp on mnist1.111×
  • compact-mobilenet on digits0.944×
  • compact-mobilenet on fashion0.940×
  • compact-mobilenet on mnist0.892×
  • compact-normalized_mlp on digits0.986×
  • compact-normalized_mlp on fashion0.866×
  • compact-normalized_mlp on mnist0.832×
  • compact-resnet on digits0.930×
  • compact-resnet on fashion0.958×
  • compact-resnet on mnist0.924×
  • appliance-gru on appliance-energy0.723×
  • mitbih-gru on mitbih0.884×
  • mnist-rows-lstm on mnist-rows0.822×
  • speech-commands-gru on speech-commands0.863×
  • speech-commands-lstm-gru on speech-commands0.859×
  • spoken-arabic-digit-lstm on spoken-arabic-digit0.800×
  • tiny-shakespeare-lstm on tiny-shakespeare1.002×
  • uci-har-gru on uci-har0.867×
  • uci-har-lstm on uci-har0.783×
  • uci-har-mixer on UCI-HAR1.039×
  • uci-har-mlp on UCI-HAR0.948×
  • uci-har-mobilenet on UCI-HAR0.951×
  • uci-har-normalized_mlp on UCI-HAR0.998×
  • uci-har-resnet on UCI-HAR0.964×
MLP2 runs

RunsGenerated 1.029× · real models 1.035×

MachineTime
  1. prod-amd64Seed 31540951951.020×Done1 attempt0.016× of the baseline kernels' time
  2. prod-arm64Seed 31540951951.044×Done1 attempt0.016× of the baseline kernels' time

By model and inputGuard at 1.100×

MLP

  • Batch 1, normal1.071×
  • Batch 1, sparse0.982×
  • Batch 1, wide0.998×

Real models

  • compact-mlp on digits0.537×
  • compact-mlp on fashion2.158×
  • compact-mlp on mnist1.018×
  • uci-har-mlp on UCI-HAR0.971×
ResNet2 runs

RunsGenerated 0.971× · real models 0.952×

MachineTime
  1. prod-amd64Seed 31540951950.975×Done1 attempt0.008× of the baseline kernels' time
  2. prod-arm64Seed 31540951950.948×Done1 attempt0.008× of the baseline kernels' time

By model and inputGuard at 1.100×

ResNet

  • Batch 1, normal0.991×
  • Batch 1, sparse0.944×
  • Batch 1, wide0.968×

Real models

  • compact-resnet on digits0.978×
  • compact-resnet on fashion0.954×
  • compact-resnet on mnist0.920×
  • uci-har-resnet on UCI-HAR0.957×
MobileNet2 runs

RunsGenerated 1.181× · real models 0.960×

MachineTime
  1. prod-amd64Seed 31540951950.977×Done1 attempt0.012× of the baseline kernels' time
  2. prod-arm64Seed 31540951951.161×Done1 attempt0.012× of the baseline kernels' time

By model and inputGuard at 1.100×

MobileNet

  • Batch 1, normal1.427×
  • Batch 1, sparse0.990×
  • Batch 1, wide0.925×

Real models

  • compact-mobilenet on digits0.839×
  • compact-mobilenet on fashion0.954×
  • compact-mobilenet on mnist0.941×
  • uci-har-mobilenet on UCI-HAR1.129×
Normalized MLP2 runs

RunsGenerated 0.978× · real models 1.051×

MachineTime
  1. prod-amd64Seed 31540951950.983×Done1 attempt0.007× of the baseline kernels' time
  2. prod-arm64Seed 31540951951.046×Done1 attempt0.013× of the baseline kernels' time

By model and inputGuard at 1.100×

Normalized MLP

  • Batch 1, normal1.031×
  • Batch 1, sparse1.087×
  • Batch 1, wide1.048×

Real models

  • compact-normalized_mlp on digits0.766×
  • compact-normalized_mlp on fashion0.897×
  • compact-normalized_mlp on mnist1.713×
  • uci-har-normalized_mlp on UCI-HAR1.037×
Mixer2 runs

RunsGenerated 1.061× · real models 1.150×

MachineTime
  1. prod-amd64Seed 31540951950.985×Done1 attempt0.004× of the baseline kernels' time
  2. prod-arm64Seed 31540951951.238×Done1 attempt0.004× of the baseline kernels' time

By model and inputGuard at 1.100×

Mixer

  • Batch 1, normal1.124×
  • Batch 1, sparse1.028×
  • Batch 1, wide1.161×

Real models

  • appliance-energy-mixer on Appliance Energy Prediction0.877×
  • compact-mixer on digits2.234×
  • compact-mixer on fashion0.988×
  • compact-mixer on mnist0.997×
  • uci-har-mixer on UCI-HAR1.042×
Recurrent2 runs

RunsGenerated 1.031× · real models 0.956×

MachineTime
  1. prod-amd64Seed 31540951951.021×Done1 attempt0.009× of the baseline kernels' time
  2. prod-arm64Seed 31540951950.966×Done1 attempt0.010× of the baseline kernels' time

By model and inputGuard at 1.100×

Recurrent

  • Batch 1, normal1.036×
  • Batch 1, sparse1.058×
  • Batch 1, wide1.057×

Real models

  • appliance-gru on appliance-energy1.038×
  • mitbih-gru on mitbih0.938×
  • mnist-rows-lstm on mnist-rows0.971×
  • speech-commands-gru on speech-commands0.991×
  • speech-commands-lstm-gru on speech-commands0.963×
  • spoken-arabic-digit-lstm on spoken-arabic-digit0.899×
  • tiny-shakespeare-lstm on tiny-shakespeare0.957×
  • uci-har-gru on uci-har0.958×
  • uci-har-lstm on uci-har0.900×