argfa/bc3-gpu repository overview

⁠ArgfaMining BC3 (BitcoinIII) GPU Miner — AURORA-FUSION

Official GPU miner for BitcoinIII (BC3) — post-fork SHA3-256t — built for the ArgfaMining⁠ pool. Native multi-GPU: one process drives every supported card in the rig (single worker, summed hashrate).

⁠What's new in 5.5.2 — a failed start now tells you what is missing

No kernel or engine changes: same hashrate as 5.5.0. What changed is everything around a start that does not work.

• An unknown REGION is refused instead of quietly falling back to usa — and the city name works now (frankfurt, mumbai, virginia).
• When no GPU can be used, the log prints the NVIDIA driver you have and the one this image needs (R580 — it ships CUDA 13). Before, it listed your cards and then said no GPU detected with nothing else.
• Datacenter cards no longer report themselves as PTX fallback while running a native kernel.

⁠What came in 5.5.0 — datacenter GPUs now mine

The image ships native code for eight NVIDIA architectures instead of four. If you rent GPUs, this is the release that matters: the datacenter cards on vast.ai, RunPod and octa.space were detected before but could not mine — the binary had no kernel for them.

Newly supported:

Already supported, unchanged: RTX 20xx / GTX 16xx / T4 (75), RTX 30xx (86), RTX 40xx (89), RTX 50xx (120).

These are natively compiled kernels, not JIT — full speed from the first second, no warm-up compile. Mining behaviour is unchanged on cards that already worked: same kernel, same hashes, same speed.

⁠What came in 5.3.0 — your address is checked before you mine

The miner verifies the checksum of your payout address, not just its shape, and refuses to start if a single character is wrong. A mistyped address still looks perfectly valid (right prefix, right length) but nobody can pay it: your shares count, your hashrate shows on the dashboard, and the reward never arrives.

Check any address without starting the miner:

docker run --rm argfa/bc3-gpu:latest --check-address <your address>

It prints the address type and exits 0 when valid.

Also fixed in 5.3.0: duplicate shares that the pool rejected while auto-tune was stepping through intensity levels.

⁠What came in 5.2.0 — mixed NVIDIA+AMD rigs

The miner enumerates CUDA and OpenCL GPUs in a single unified list and runs CUDA + OpenCL contexts in the same process: rigs mixing NVIDIA and AMD cards mine with all of them (per-backend boot self-test; iGPUs are listed but deselected by default; true AMD multi-GPU). Inside Docker, --gpus injects the NVIDIA driver only, so the mixed-rig case applies to the native Linux/Windows builds for now (ROCm base image pending).

⁠Quick start

docker run --rm --gpus all \
  -e WALLET=your_bc3_address \
  -e WORKER=rig1 \
  -e MODE=prop \
  -e REGION=usa \
  argfa/bc3-gpu:latest

⁠Renting on a platform that builds the run command for you

On clore.ai, Salad, TensorDock and similar, you pick an image and fill a form — you never write the docker run, so there is no --gpus all to add. GPU access there is driven by environment variables, and the two below are the ones that matter. Set them next to WALLET / WORKER / MODE / REGION:

NVIDIA_VISIBLE_DEVICES=all
NVIDIA_DRIVER_CAPABILITIES=compute,utility

The image already declares both, but these platforms build their own run command and the image's values do not always survive it. Setting them explicitly costs nothing.

If the miner exits immediately with exit 127, that is the NVIDIA driver not reaching the container — libcuda.so.1 and libnvidia-ml.so.1 come from the host and are not inside the image. Confirm it in one command:

docker run --rm --entrypoint nvidia-smi argfa/bc3-gpu:latest

If that fails inside the container the problem is the GPU passthrough, not the miner.

⁠Configuration (environment variables)

Regions: latam (Venezuela) · usa (Virginia) · eu (Frankfurt) · in (Mumbai, India).

BC3 accepts all five address formats: 1… (P2PKH), 3… (P2SH), bc1q… (P2WPKH/P2WSH), bc1p… (P2TR).

⁠Multi-GPU

By default the miner uses all supported GPUs. Pin specific cards with -e DEVICES=0,1. Any extra arguments after the image name pass straight to the miner.

⁠Requirements (host)

• NVIDIA driver R580 or newer (the minimum for CUDA 13, which this image uses) + nvidia-container-toolkit. Both are pre-installed on vast.ai / RunPod / octa.space, but check the driver on the offer before you rent. On platforms where you don't write the docker run (clore.ai, Salad, TensorDock), see the note above the configuration table.
• GPU: NVIDIA sm_75 or newer — Turing, Ampere (incl. A100), Ada, Hopper (H100/H200) and Blackwell (RTX 50xx and B100/B200/B300). AMD via OpenCL (mixed NVIDIA+AMD rigs supported by the miner binary; in Docker the AMD runtime needs a ROCm base — pending).
• Pre-Turing cards (GTX 10xx and older) are not supported here: NVIDIA removed them from the toolkit this build requires. Use our HiveOS package for those.
• Tiny ubuntu:22.04 base (~143 MB); the CUDA runtime (libcudart.so.13) ships inside the image and the driver is injected at runtime by --gpus.

⁠Validation

On start it prints the kernel self-test per backend — it must say PASS. In the stats lines, verify_fail must stay 0 and accepted shares (acc) should climb.

⁠Notes

• Tags: 5.5.2 (pinned) · latest.
• Pool-locked: this image mines exclusively to ArgfaMining; the region selects the endpoint.

Support: https://discord.gg/nZTu2QC2YC⁠