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Sometimes—but there is no official evidence that XMRig is always faster than competing Monero miners. Its RandomX hashrate depends heavily on CPU cache, memory bandwidth, NUMA layout, and whether settings such as huge pages and MSR are active. The useful answer to “Is XMRig faster?” is to compare miners on the same system, algorithm, and sustained workload.
What XMRig does—and what its documentation does not claim
The XMRig project describes XMRig as an open-source, cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight, and GhostRider, as well as a RandomX benchmark. Its official overview lists Windows, Linux, macOS, and FreeBSD binaries (XMRig miner overview). That establishes what the software supports; it does not establish that XMRig beats every other Monero miner.
For Monero, the algorithm entry to compare is rx/0, which XMRig identifies as RandomX (Monero) in its algorithm list. A result using a different algorithm variant or benchmark mode is not a like-for-like comparison.
Why one system may get a faster result than another
CPU cache limits useful thread count
RandomX is sensitive to cache capacity. XMRig’s optimization guide specifies 2 MB of L3 cache per mining thread, alongside 256 KB of L2 cache per thread. When available cache is constrained, activating every CPU thread may not improve hashrate: the additional threads compete for resources the workload needs. A CPU with enough L3 cache per mining thread can matter more than simply choosing the highest thread count (RandomX Optimization Guide).
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Memory capacity and bandwidth affect throughput
The same guide specifies 2080 MB of dataset memory per NUMA node and 256 MB of cache on the first NUMA node. It also gives approximate per-channel limits of 1500–2000 H/s for DDR3 and 4000–6000 H/s for DDR4, depending on frequency and timings. These are XMRig project’s guidance, with no publication year stated on the page; they are not universal predictions for every motherboard, CPU, or workload.
Memory channels, frequency, and timings can therefore constrain a system even when the CPU has spare threads. A compatible dual-channel RAM kit is relevant only if the system’s memory configuration is a measured bottleneck; compatibility and the actual channel layout matter.
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NUMA configuration matters on multi-node systems
XMRig says disabling NUMA uses one dataset and significantly reduces hashrate on multi-node systems. On a machine with only one NUMA node, disabling NUMA has no effect. The distinction means the same setting should not be expected to help or hurt every PC equally.
Huge pages and MSR may help, but gains are conditional
XMRig’s documentation says huge pages may increase RandomX performance by up to 50%; Linux 1 GB huge pages may add 1–3% beyond regular huge pages. The project also says MSR modification may provide up to 15% speedup, depending on the system. These are conditional estimates from XMRig, not guaranteed gains or independent head-to-head test results. The benchmark output can show whether huge pages are active for the dataset and threads and whether MSR values were set successfully; XMRig warns that results may be far from best when these settings are not properly applied (optimization guide; benchmark guide).
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Other workloads can change the result
Mining alongside other programs can introduce interference. XMRig documents cache QoS as experimental and useful for reducing interference when mining on fewer than all cores; it should not be treated as a universal speed setting.
How to compare XMRig fairly on your machine
- Record the setup. Note the CPU model, memory capacity and channel layout, operating system, XMRig version, algorithm, and benchmark mode. Keep the machine and algorithm the same when comparing settings or miners.
- Run a built-in benchmark. In a terminal, run
xmrig --bench=1Mfor a shorter run orxmrig --bench=10Mfor a longer one. Online submission requires adding--submit; leave it off for an offline run. RandomX v2 benchmark mode requires XMRig 6.26.0 or newer, so check that requirement if using that mode rather than assuming every XMR benchmark is v2 (XMRig benchmark documentation). - Check whether optimizations took effect. Read the displayed huge-page status for both dataset and threads, and the MSR status. A setting that was not applied cannot explain a performance difference.
- Check computation stability. For an offline benchmark, inspect the checksum: XMRig says green indicates correct computation and red indicates a hardware error. Its documentation notes that offline benchmarks can check hardware stability without an internet connection.
- Compare sustained results. Repeat runs under consistent conditions and compare their sustained results, not one context-free hashrate number. Record configuration and stability alongside speed so a faster-looking result is not mistaken for a dependable one.
What a useful miner comparison should include
| Comparison axis | What to check |
|---|---|
| Hashrate | Same machine, algorithm variant, version context, and benchmark mode. |
| Stability | Repeatability and valid offline checksum. |
| Configuration | Whether huge pages and MSR were successfully applied, plus the effort and permissions needed to configure them. |
| Hardware fit | Cache per thread, memory capacity and bandwidth, memory channel layout, and NUMA topology. |
XMRig’s official documentation does not provide a controlled, like-for-like comparison against named competing miners, so it cannot establish a general software winner. A measured comparison on the reader’s own hardware is the sound basis for deciding which configuration performs better.
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