Current averages, ranks, sample depth, and data freshness.
| DATA SAMPLES INFO Filter applied, PPD samples all time |
AVERAGE FOLDING PERFORMANCE Based on ALL available PPD samples by filter |
WORK UNIT PPD RECORDS All Time |
|||||
|---|---|---|---|---|---|---|---|
| OS FILTER | SAMPLES | PPD | WU Per 24hrs | Time Per WU | Points Per WU | BEST PPD | WORST PPD |
| All OS AVG | 216,119 | 1,172,660 | 6.20 | 3 hrs 52 mins | 189,186 | 338,278,539 | 8,520 |
| Linux | 44,585 | 1,324,515 | 6.03 | 3 hrs 59 mins | 219,800 | 5,730,617 | 217,163 |
| Windows | 171,534 | 1,133,190 | 6.25 | 3 hrs 50 mins | 181,229 | 338,278,539 | 8,520 |
Launch the LAR.SYSTEMS V8 Web Client to monitor live work-unit activity, compare your machine with community benchmarks, and contribute real samples that keep public rankings and hardware insights current for the Folding@Home community.
| Sample | Folder | Team | Platform | Seen |
|---|---|---|---|---|
| Most recent WU sample | $brilliant | Ukraine | Windows GPU | 5 days ago |
| First seen | agentclank777 | Savage Solutions Global | Windows GPU | Not recorded |
Use the range, net change, and latest average as a quick signal—not a final judgment on the GPU.
Values use the same weekly community averages as the detailed chart.
GPU PPD average changes week to week for a number of reasons such as credit for type of projects/causes available, variance in work unit difficulty, OS/GPU drivers, folding cores, GPU models, clocks, power targets etc.
The chart below serves as a way to see historical week to week performance change as PPD for a GPU is never a constant, as the work units processed are always changing.
Average PPD is impacted by the types of research work units being done as they return different amounts of points and take different amounts of time.
The following shows the work unit allocation of research causes to better understand changes in PPD over time for the GeForce GTX 1660 SUPER.
| Research | Percent |
|---|---|
| No Data For This Reporting Period. | |
| Research | Percent |
|---|---|
|
ENZYME DYNAMICS |
72.55% |
|
NIPAH VIRUS DECOY PROTEIN DYNAMICS |
27.45% |
| Research | Percent |
|---|---|
|
ENZYME DYNAMICS |
75.87% |
|
ATSTP10 TRANSPORT SIMULATION |
12.61% |
|
ATSTP10 SUCROSE TRANSPORT |
5.87% |
|
NIPAH VIRUS DECOY PROTEIN DYNAMICS |
5.65% |
The following visualization illustrates the PPD / Credit allocation of work units across different research causes, providing insight into how PPD varies by work unit PPD samples for the GeForce GTX 1660 SUPER.
This analysis helps better understand the relationship between research causes and PPD/Credit, highlighting any performance trends as clusters or anomalies as outliers.
Power consumption information for the GeForce GTX 1660 SUPER is based on an average wattage taken from vendor information for the lowest and highest power draws for the GPU under Folding@Home compute loads.
Wattage information is only for the GPU and does not include the host computer's power usage.
| GPU Power Draw Watts - TDP |
Daily Power Usage kWh |
Points per kWh |
Daily Cost at $0.10 per kWh |
Power Cost per 1m Points |
|---|---|---|---|---|
| 125 W | 3.00 kWh | 777,046 | $0.30 | $0.129 |
Folding@Home compute projections for the GeForce GTX 1660 SUPER can be used to help inform long-term point goals and related costs based on 24/7 usage.
| Duration | Nickname | Points Average |
Work Units Average |
Power Usage kWh |
Power Cost at $0.10 per kWh |
|---|---|---|---|---|---|
| Day | PPD | 2,331,138 | 32.89 | 3.00 kWh | $0.30 |
| Week | PPW | 16,317,966 | 230.21 | 21.00 kWh | $2.10 |
| Month | PPM | 70,905,447 | 1000.32 | 91.25 kWh | $9.13 |
| Year | PPY | 850,865,370 | 12003.80 | 1095.00 kWh | $109.50 |
| PPD Rank | Project ID | Cause Research | PPD Average | Points WU Average | WUs Day Average | WU Time Average |
|---|---|---|---|---|---|---|
| 1 | 17919 | Malaria | 11,665,999 | 209,588 | 55.66 | 0 hrs 26 mins |
| 2 | 15414 | enzyme-dynamics | 4,479,953 | 35,599 | 125.84 | 0 hrs 11 mins |
| 3 | 12112 | Peptide-Conformation-Modeling | 4,126,128 | 57,239 | 72.09 | 0 hrs 20 mins |
| 4 | 12110 | Peptide-Conformation-Modeling | 4,082,169 | 56,648 | 72.06 | 0 hrs 20 mins |
| 5 | 12111 | Peptide-Conformation-Modeling | 3,976,793 | 57,312 | 69.39 | 0 hrs 21 mins |
| PPD Rank | Project ID | Cause Research | PPD Average | Points WU Average | WUs Day Average | WU Time Average |
|---|---|---|---|---|---|---|
| 1 | 18806 | cancer | 40,503 | 32,000 | 1.27 | 18 hrs 58 mins |
| 2 | 13007 | cancer | 144,309 | 99,515 | 1.45 | 16 hrs 33 mins |
| 3 | 17948 | CRISPR-Guide-RNA-Modification | 167,075 | 42,996 | 3.89 | 6 hrs 11 mins |
| 4 | 15310 | cancer | 191,950 | 13,926 | 13.78 | 1 hrs 44 mins |
| 5 | 18235 | Force-Field-Protein-Dynamics | 219,815 | 71,964 | 3.05 | 7 hrs 51 mins |
