RGminer v1.0.0
21.07.2026
Highlights
- Added new CUDA kernels for NVIDIA SM70, SM90, and SM100 architectures.
- Fixed Kryptex pool connectivity and protocol handling.
- Better compatibility with A100/CMP 170HX
Pearl Performance
| GPU | Architecture | OC Profile | Hashrate | Power | Efficiency | Energy Usage |
|---|---|---|---|---|---|---|
| Tesla V100-SXM2-16GB | Volta | 0 / 1550 / 0 |
49.5 TH/s | 280 W | 0.176 TH/W | 5.66 W/TH |
| RTX 2080 | Turing | 125 / 1650 / 5000 |
44.16 TH/s | 160 W | 0.276 TH/W | 3.62 W/TH |
| RTX 3070m | Ampere | 250 / 1650 / 6000 |
65.3 TH/s | 140 W | 0.466 TH/W | 2.14 W/TH |
| RTX 3070 | Ampere | 250 / 1450 / 6000 |
66.5 TH/s | 130 W | 0.512 TH/W | 1.95 W/TH |
| CMP 170HX/A100 | Ampere | 250 / 1450 / 0 |
160 TH/s | 210 W | 0.761 TH/W | 1.31 W/TH |
| RTX 4070 Ti | Ada | 350 / 2450 / 5000 |
145.3 TH/s | 190 W | 0.765 TH/W | 1.31 W/TH |
| RTX 5070 Ti | Blackwell | 490 / 2450 / 7000 |
160.7 TH/s | 218 W | 0.724 TH/W | 1.38 W/TH |
Miner Watchdog
The watchdog controls how rgminer responds to critical CUDA errors.
--watchdog=off - disables automatic rig rebooting and persistent GPU disabling.
--watchdog=restart - restart on errors
--watchdog=reboot - reboot on errors
GPU Clock Control
Each option accepts multiple GPUs using:
GPU_INDEX:VALUE,GPU_INDEX:VALUE
./rgminer \
--cclock 0:125,1:250 \
--mclock 0:500,1:1000 \
--lock-cclock 0:1650,1:2450 \
--lock-mclock 0:7000,1:7000 \
...
New Pearl Pool Protocols
Added support for three Pearl pool protocols:
- PearlFortune —
--proto pearlfortune - AlphaPool —
--proto alphapool - f2pool —
--proto f2pool
Pool-specific Stratum authorization, job parsing and share submission are supported.
Compressed share submission is also supported where required:
- PearlFortune/herominers — zstd-compressed proofs
- f2pool/kryptex — gzip-compressed v2 shares
Complete Launch Example
./rgminer \
--algo pearl \
--stratum POOL:PORT \
--wallet WALLET \
--worker RIG_NAME \
Backend policy
- Turing, Ampere and Ada builds are shipped on CUDA 12.4
- Blackwell build is shipped on CUDA 12.8
Performance depends on GPU model, driver, clocks, memory and power limit conditions.