Entry #48
Completed- Hotkey
- 5FFZdM…hknaNw
- Sent
- 11 Nov 2026, 12:21 UTC
- Source
- 90c4f685404f
Progress
- Queued
- Proof
- Planned
- Timing
- Done
Done means every board has a decision. It does not mean the entry took a board over.
On each board
| Board | Runs | Time | Decision |
|---|---|---|---|
| Overallvs #43 | Done2 of 2 runs | 0.974×Generated 0.975×, real models 0.974× | Above the barGain lower bound -6.0%Guard passed |
| MLPvs #44 | Done2 of 2 runs | 0.884×Generated 1.002×, real models 0.780× | Not significantGain lower bound -24.7%Guard passed |
| ResNetvs #45 | Done2 of 2 runs | 1.011×Generated 0.981×, real models 1.042× | Above the barGain lower bound -4.8%Guard passed |
| MobileNetvs #42 | Done2 of 2 runs | 1.120×Generated 1.138×, real models 1.102× | Above the barGain lower bound -38.6%Guard passed |
| Normalized MLPvs #48 | Done2 of 2 runs | 1.126×Generated 1.092×, real models 1.162× | Above the barGain lower bound -38.1%Guard passed |
| Mixervs #47 | Done2 of 2 runs | 1.029×Generated 1.200×, real models 0.882× | Above the barGain lower bound -17.0%Guard passed |
| Recurrentvs #46 | Done2 of 2 runs | 1.008×Generated 0.968×, real models 1.051× | Above the barGain lower bound -2.2%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 0.975× · real models 0.974×
- prod-amd64Seed 16615100900.986×Done1 attempt0.009× of the baseline kernels' time
- prod-arm64Seed 16615100900.963×Done1 attempt0.011× of the baseline kernels' time
By model and inputGuard at 1.100×
MLP
- Batch 1, normal0.982×
- Batch 1, sparse0.979×
- Batch 1, wide1.019×
Mixer
- Batch 1, normal0.969×
- Batch 1, sparse0.977×
- Batch 1, wide0.964×
ResNet
- Batch 1, normal0.961×
- Batch 1, sparse0.969×
- Batch 1, wide0.957×
MobileNet
- Batch 1, normal1.003×
- Batch 1, sparse0.998×
- Batch 1, wide0.966×
Recurrent
- Batch 1, normal0.951×
- Batch 1, sparse0.946×
- Batch 1, wide0.964×
Normalized MLP
- Batch 1, normal0.961×
- Batch 1, sparse0.992×
- Batch 1, wide1.251×
Real models
- appliance-energy-mixer on Appliance Energy Prediction0.908×
- compact-mixer on digits0.930×
- compact-mixer on fashion0.976×
- compact-mixer on mnist0.979×
- compact-mlp on digits0.833×
- compact-mlp on fashion0.764×
- compact-mlp on mnist1.021×
- compact-mobilenet on digits1.269×
- compact-mobilenet on fashion0.992×
- compact-mobilenet on mnist1.036×
- compact-normalized_mlp on digits0.921×
- compact-normalized_mlp on fashion1.081×
- compact-normalized_mlp on mnist0.727×
- compact-resnet on digits1.242×
- compact-resnet on fashion0.953×
- compact-resnet on mnist0.949×
- appliance-gru on appliance-energy0.948×
- mitbih-gru on mitbih0.947×
- mnist-rows-lstm on mnist-rows1.160×
- speech-commands-gru on speech-commands0.942×
- speech-commands-lstm-gru on speech-commands0.952×
- spoken-arabic-digit-lstm on spoken-arabic-digit0.952×
- tiny-shakespeare-lstm on tiny-shakespeare0.990×
- uci-har-gru on uci-har0.945×
- uci-har-lstm on uci-har0.951×
- uci-har-mixer on UCI-HAR0.976×
- uci-har-mlp on UCI-HAR0.997×
- uci-har-mobilenet on UCI-HAR1.056×
- uci-har-normalized_mlp on UCI-HAR1.030×
- uci-har-resnet on UCI-HAR0.956×
MLP2 runs
RunsGenerated 1.002× · real models 0.780×
- prod-amd64Seed 16615100900.941×Done1 attempt0.013× of the baseline kernels' time
- prod-arm64Seed 16615100900.831×Done1 attempt0.022× of the baseline kernels' time
By model and inputGuard at 1.100×
MLP
- Batch 1, normal1.014×
- Batch 1, sparse1.006×
- Batch 1, wide1.223×
Real models
- compact-mlp on digits0.432×
- compact-mlp on fashion1.049×
- compact-mlp on mnist0.793×
- uci-har-mlp on UCI-HAR1.029×
ResNet2 runs
RunsGenerated 0.981× · real models 1.042×
- prod-amd64Seed 16615100901.011×Done1 attempt0.008× of the baseline kernels' time
- prod-arm64Seed 16615100901.011×Done1 attempt0.009× of the baseline kernels' time
By model and inputGuard at 1.100×
ResNet
- Batch 1, normal0.970×
- Batch 1, sparse0.975×
- Batch 1, wide0.992×
Real models
- compact-resnet on digits1.285×
- compact-resnet on fashion0.973×
- compact-resnet on mnist0.955×
- uci-har-resnet on UCI-HAR0.985×
MobileNet2 runs
RunsGenerated 1.138× · real models 1.102×
- prod-amd64Seed 16615100901.038×Done1 attempt0.012× of the baseline kernels' time
- prod-arm64Seed 16615100901.208×Done1 attempt0.012× of the baseline kernels' time
By model and inputGuard at 1.100×
MobileNet
- Batch 1, normal1.352×
- Batch 1, sparse1.007×
- Batch 1, wide1.010×
Real models
- compact-mobilenet on digits1.288×
- compact-mobilenet on fashion0.992×
- compact-mobilenet on mnist1.038×
- uci-har-mobilenet on UCI-HAR1.110×
Normalized MLP2 runs
RunsGenerated 1.092× · real models 1.162×
- prod-amd64Seed 16615100901.064×Done1 attempt0.007× of the baseline kernels' time
- prod-arm64Seed 16615100901.192×Done1 attempt0.016× of the baseline kernels' time
By model and inputGuard at 1.100×
Normalized MLP
- Batch 1, normal1.291×
- Batch 1, sparse1.025×
- Batch 1, wide1.028×
Real models
- compact-normalized_mlp on digits1.211×
- compact-normalized_mlp on fashion1.082×
- compact-normalized_mlp on mnist1.190×
- uci-har-normalized_mlp on UCI-HAR1.167×
Mixer2 runs
RunsGenerated 1.200× · real models 0.882×
- prod-amd64Seed 16615100901.145×Done1 attempt0.005× of the baseline kernels' time
- prod-arm64Seed 16615100900.925×Done1 attempt0.005× of the baseline kernels' time
By model and inputGuard at 1.100×
Mixer
- Batch 1, normal1.205×
- Batch 1, sparse1.411×
- Batch 1, wide1.281×
Real models
- appliance-energy-mixer on Appliance Energy Prediction1.100×
- compact-mixer on digits0.449×
- compact-mixer on fashion1.013×
- compact-mixer on mnist1.023×
- uci-har-mixer on UCI-HAR1.041×
Recurrent2 runs
RunsGenerated 0.968× · real models 1.051×
- prod-amd64Seed 16615100900.995×Done1 attempt0.012× of the baseline kernels' time
- prod-arm64Seed 16615100901.021×Done1 attempt0.013× of the baseline kernels' time
By model and inputGuard at 1.100×
Recurrent
- Batch 1, normal0.951×
- Batch 1, sparse0.983×
- Batch 1, wide0.969×
Real models
- appliance-gru on appliance-energy1.100×
- mitbih-gru on mitbih1.034×
- mnist-rows-lstm on mnist-rows1.193×
- speech-commands-gru on speech-commands1.043×
- speech-commands-lstm-gru on speech-commands1.015×
- spoken-arabic-digit-lstm on spoken-arabic-digit0.997×
- tiny-shakespeare-lstm on tiny-shakespeare1.040×
- uci-har-gru on uci-har1.028×
- uci-har-lstm on uci-har1.017×