Folding@home GPUs PPD Price Watt


1	Last update 2020-09-02 for FahCore_22 OpenCL * Please check the values yourself and don't trust the chart blindly. See more infos below.
2	GPU	PPD in k	Price in $	Watt	PPD/Price	PPD/Watt

3	RTX 3090	5000	1500	375	3,3	13,3	needs large work units to get fully utilized
4	RTX 3080	4000	700	320	5,7	12,5	needs large work units to get fully utilized
5	RTX 3070	2500	500	220	5,0	11,4	needs large work units to get fully utilized
6	RTX 3060	2000	350	150
7	Titan RTX	2400	2500	300	1,0	8,0	needs large work units to get fully utilized
8	RTX 2080ti	2400	1100	300	2,2	8,0	needs large work units to get fully utilized
9	RTX 2080 Super	2000	710	250	2,8	8,0
10	RTX 2080	1800	620	225	2,9	8,0
11	RTX 2070 Super	1600	500	200	3,2	8,0
12	RTX 2070	1400	400	175	3,5	8,0
13	RTX 2060 Super	1275	400	160	3,2	8,0
14	RTX 2060	1160	320	145	3,6	8,0
15	GTX 1660 Ti	875	300	110	2,9	8,0
16	GTX 1660 (or Super)	800	250	100	3,2	8,0
17	GTX 1650 Super	715	190	89	3,8	8,0
18	GTX 1650	500	170	62	2,9	8,1
19	Titan V	1500	3000	250	0,5	6,0
20	Titan X Pascal	1500	1000	250	1,5	6,0
21	GTX 1080 Ti	1500	800	250	1,9	6,0	P102-100 mining
22	GTX 1080	1075	600	180	1,8	6,0	P104-100 mining
23	GTX 1070 Ti	1000	500	180	2,0	5,6
24	GTX 1070	850	300	150	2,8	5,7	single slot model available
25	GTX 1060 6GB	480	270	90	1,8	5,3	P106-100 mining
26	GTX 1060 3GB	420	230	81	1,8	5,2
27	GTX 1050Ti	250	150	60	1,7	4,2	P106-090 mining, no power plug needed, low profile available
28	GTX 1050	200	130	50	1,5	4,0	no power plug needed, low profile available
29	GT 1030	62	100	30	0,6	2,1	no power plug needed, single slot low profile available
30	AMD RX 6000 16GB	3000	500	300	6,0	10,0	not yet released (end of 2020)
31	AMD RX 5700 XT	1350	400	200	3,4	6,8	needs large work units to get fully utilized
32	AMD RX 5600 XT	1000	300	150	3,3	6,7	needs large work units to get fully utilized
33	AMD RX 5500 XT	680	200	100	3,4	6,8	needs large work units to get fully utilized
34	AMD Radeon VII 16GB	1500	700	300	2,1	5,0	needs large work units to get fully utilized
35	Vega Frontier Edition	1000	915	300	1,1	3,3	needs large work units to get fully utilized
36	RX Vega 64	1000	400	300	2,5	3,3	needs large work units to get fully utilized
37	RX Vega 56	700	300	210	2,3	3,3	needs large work units to get fully utilized
38	RX 590 8GB	470	200	150	2,4	3,1
39	RX 580 4GB	450	180	150	2,5	3,0
40	RX 570 4GB	330	120	110	2,8	3,0
41	RX 560 2GB	200	100	80	2,0	2,5
42	RX 550 2GB	90	85	50	1,1	1,8	no power plug needed, low profile available
43
44	Older generation with refurbished prices
45	Titan X Maxwell	875	950	230	0,9	3,8
46	GTX 980Ti	875	425	277	2,1	3,2
47	GTX 980	550	330	205	1,7	2,7
48	GTX 970	440	220	170	2,0	2,6
49	GTX 960 2GB	225	120	150	1,9	1,5
50	GTX 950	140	125	110	1,1	1,3
51	GTX 750Ti	100	100	70	1,0	1,4	no power plug needed
52	RX 480 4GB	390	500	130	0,8	3,0
53	RX 470	320	650	105	0,5	3,0
54	RX 460 2GB	180	135	60	1,3	3,0	no power plug needed, low profile or single slot available
55	Fury X	550	380	275	1,4	2,0
56	R9 Fury	412	260	250	1,6	1,6
57	R9 390X	465	365	250	1,3	1,9
58	R9 380X	174	220	190	0,8	0,9
59	R9 290	325	380	275	0,9	1,2
60	R9 280X / HD 7970	160	200	200	0,8	0,8
61
62	* Please check the values yourself and don't trust the chart blindly.
63	* Based on FahCore_22 OpenCL (older GPU core were 25% slower, future CUDA core will be 25% faster)
64	* PPD, Price and Watt will vary on different vendor custom models.
65	* Limit GPU power usage with tools like MSI Afterburner to increae efficiency
66	* For new released GPUs the values are predicted due to hw specs.
67	* You will not get max PPD with every folding work unit or project.
68	* Linux is 20% faster than Windows
69	* Each GPU needs one cpu thread to feed it.
70	* On Windows pcie 3.0 x8 is needed for full performance of fast GPUs, x4 is minimum. On Linux for full performance x4 is optimum. x1 risers are 20% slower on Linux and more than 50% on Windows
71
72	Source:
73	https://foldingforum.org/viewtopic.php?f=38&t=29322
74	http://www.overclock.net/t/475163/gpu-projects-ppd-database
75	https://folding.lar.systems/folding_data/gpu_ppd_overall