<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Vps – Serverküche</title><link>https://serverkueche.de/en/tags/vps/</link><description>Vps – Neueste Beiträge von Serverküche</description><generator>Hugo</generator><language>en-US</language><managingEditor>feedback@serverkueche.de (Serverküche)</managingEditor><webMaster>feedback@serverkueche.de (Serverküche)</webMaster><copyright>2026 Serverküche</copyright><lastBuildDate>Tue, 28 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://serverkueche.de/en/tags/vps/index.xml" rel="self" type="application/rss+xml"/><item><title>netcup VPS 1000 G12 benchmarked: how fast is it really?</title><link>https://serverkueche.de/en/tutorials/netcup-vps-1000-benchmark/</link><pubDate>Tue, 28 Jul 2026 00:00:00 +0000</pubDate><author>feedback@serverkueche.de (Serverküche)</author><guid>https://serverkueche.de/en/tutorials/netcup-vps-1000-benchmark/</guid><description>Real benchmark figures for the netcup VPS 1000 G12: CPU, RAM, NVMe and network – measured with sysbench and fio, including the commands to re-measure.</description><content:encoded><![CDATA[<p>The <a href="/en/netcup-recommendation/">VPS 1000 G12</a> is netcup&rsquo;s entry-level VPS and the server most
Serverküche recipes run on. But how fast is it <strong>really</strong>? We measured it thoroughly with
standard tools – and show you the commands you can use to check your own server against
it.</p>
<h2 id="what-are-we-measuring">What are we measuring?</h2>
<p>We benchmark the four things that matter in everyday self-hosting: <strong>CPU</strong>, <strong>memory</strong>,
<strong>NVMe disk</strong> and <strong>network</strong> – each with established open-source tools (<code>sysbench</code>,
<code>fio</code>, <code>7z</code>, <code>openssl</code>, <code>curl</code>). All figures below come from a <strong>real VPS 1000 G12</strong> on
Debian 13. The test machine: <strong>AMD EPYC-Genoa, 4 vCore, 8 GB RAM, 256 GB NVMe.</strong></p>
<p>The key figures at a glance:</p>
<table>
	<thead>
			<tr>
					<th>Area</th>
					<th>Measurement (VPS 1000 G12)</th>
			</tr>
	</thead>
	<tbody>
			<tr>
					<td>CPU – 1 core (sysbench)</td>
					<td><strong>1,495</strong> events/s</td>
			</tr>
			<tr>
					<td>CPU – 4 cores (sysbench)</td>
					<td><strong>5,974</strong> events/s (≈ 4× scaling)</td>
			</tr>
			<tr>
					<td>7-Zip (<code>7z b</code>)</td>
					<td><strong>~27,400</strong> MIPS total</td>
			</tr>
			<tr>
					<td>AES-256-GCM (AES-NI)</td>
					<td><strong>~7.7 GB/s</strong></td>
			</tr>
			<tr>
					<td>RAM throughput</td>
					<td><strong>~30 GB/s</strong></td>
			</tr>
			<tr>
					<td>NVMe – 4K random read</td>
					<td><strong>101,000</strong> IOPS</td>
			</tr>
			<tr>
					<td>NVMe – 4K random write</td>
					<td><strong>67,000</strong> IOPS</td>
			</tr>
			<tr>
					<td>NVMe – sequential read</td>
					<td><strong>4.3 GB/s</strong></td>
			</tr>
			<tr>
					<td>NVMe – sequential write</td>
					<td><strong>3.1 GB/s</strong></td>
			</tr>
			<tr>
					<td>Download (Falkenstein)</td>
					<td><strong>~246 MB/s</strong> (about 2 Gbit/s)</td>
			</tr>
			<tr>
					<td>Latency (Anycast resolver 1.1.1.1)</td>
					<td><strong>~12 ms</strong></td>
			</tr>
			<tr>
					<td>Steal time (in the test)</td>
					<td><strong>0%</strong></td>
			</tr>
	</tbody>
</table>
<p>Quick assessment: for an entry-level VPS these are consistently <strong>strong</strong> figures –
especially the NVMe disk and the network play well above what you&rsquo;d expect from the
cheapest plan. But the context matters: a VPS shares the physical CPU with other customers
(shared vCores). Your figures can differ depending on the neighbors&rsquo; load – how you spot
that is in &ldquo;When things go wrong&rdquo;.</p>
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<h2 id="prerequisites">Prerequisites</h2>
<ul>
<li>
<p>A netcup server, e.g. your <a href="/en/tutorials/first-steps-netcup-vps/">first VPS</a>, with SSH
access.</p>
</li>
<li>
<p>The benchmark tools. All are in the Debian package sources:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">sudo apt update
</span></span><span class="line"><span class="cl">sudo apt install -y sysbench fio p7zip-full</span></span></code></pre></div>
</div>
</li>
<li>
<p>Some free storage space (the disk tests write a few GB temporarily) and ideally <strong>no</strong>
production load during the measurement.</p>
</li>
</ul>
<div class="not-prose my-6 rounded-lg border-l-4 p-4 border-herb-400 bg-herb-50 dark:border-herb-700 dark:bg-herb-900/20">
  <p class="mb-1 flex items-center gap-2 font-semibold text-slate-900 dark:text-white">
    <span aria-hidden="true">🧑‍🍳</span>Measure several times
  </p>
  <div class="prose-kitchen text-sm">A single benchmark is a momentary snapshot. Run each test <strong>two or three times</strong> and
ideally at different times of day – then you see how stable the figures are.</div>
</div>
<h2 id="step-by-step">Step by step</h2>
<h3 id="step-1-size-up-the-server">Step 1: Size up the server</h3>
<p>Before you measure, look at what you&rsquo;re dealing with:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">grep -m1 <span class="s2">&#34;model name&#34;</span> /proc/cpuinfo <span class="o">&amp;&amp;</span> nproc <span class="o">&amp;&amp;</span> free -h</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">model name : AMD EPYC-Genoa Processor
</span></span><span class="line"><span class="cl">4
</span></span><span class="line"><span class="cl">               total        used        free      shared  buff/cache   available
</span></span><span class="line"><span class="cl">Mem:           7.8Gi       689Mi       3.0Gi       656Ki       4.3Gi       7.1Gi</span></span></code></pre></div>
</div>
<p>Four vCores on an <strong>AMD EPYC-Genoa</strong> (netcup&rsquo;s current G12 generation) and 8 GB RAM. Also
take a look at the <strong>steal time</strong> – the percentage the CPU &ldquo;waits&rdquo; because a neighbor on
the same host is computing:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">vmstat <span class="m">1</span> <span class="m">3</span></span></span></code></pre></div>
</div>
<p>In the <code>st</code> column (far right) it should ideally read <code>0</code>. For us it was <strong>0</strong> over the
whole test – no noticeable neighbor influence. High, persistent steal values would be the
sign of an oversubscribed host.</p>
<h3 id="step-2-cpu">Step 2: CPU</h3>
<p><code>sysbench</code> computes prime numbers – once on one core, once on all four:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">sysbench cpu --cpu-max-prime<span class="o">=</span><span class="m">20000</span> --threads<span class="o">=</span><span class="m">1</span> run
</span></span><span class="line"><span class="cl">sysbench cpu --cpu-max-prime<span class="o">=</span><span class="m">20000</span> --threads<span class="o">=</span><span class="m">4</span> run</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">1 Thread:   events per second:  1494.66
</span></span><span class="line"><span class="cl">4 Threads:  events per second:  5973.69</span></span></code></pre></div>
</div>
<p>Two things are remarkable here: the solid single-thread performance (Genoa cores are fast)
and the <strong>almost perfect scaling</strong> – 4 threads deliver 3.996× a single one. That means: at
the time of measurement, the four vCores were fully available, without neighbors siphoning
off compute time.</p>
<p>A second, practical CPU test is the built-in 7-Zip benchmark (compression, uses all
cores):</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">7z b</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">Tot:  ...  27425  (MIPS total)</span></span></code></pre></div>
</div>
<p><code>7z b</code> measures compression and decompression separately (each its own line) and combines
both in the <code>Tot:</code> line into an overall rating – that&rsquo;s the roughly <strong>27,400 MIPS</strong>. A good
reference figure to compare the VPS with other 7-Zip results online. And because encryption
runs everywhere (HTTPS, backups, VPN), the AES performance with hardware acceleration
(AES-NI):</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">openssl speed -evp aes-256-gcm</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">type             16 bytes     64 bytes    256 bytes   1024 bytes   8192 bytes  16384 bytes
</span></span><span class="line"><span class="cl">AES-256-GCM      89283.37k   343370.05k  1270428.16k  3164995.93k  7671136.75k  8464845.66k</span></span></code></pre></div>
</div>
<p><code>openssl speed</code> measures <strong>single-threaded</strong> by default – so the figure applies to one
core. For the throughput across all cores you append <code>-multi $(nproc)</code>. In our run a single
core reached about <strong>7.7 GB/s</strong> (7,671,136 k) on the 8 KB blocks. TLS is thus never the
bottleneck on this processor anyway.</p>
<h3 id="step-3-memory">Step 3: Memory</h3>
<p><code>sysbench</code> writes a large block repeatedly through RAM and measures the throughput:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">sysbench memory --memory-block-size<span class="o">=</span>1M --memory-total-size<span class="o">=</span>30G --threads<span class="o">=</span><span class="m">4</span> run</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">30720.00 MiB transferred (28727.21 MiB/sec)</span></span></code></pre></div>
</div>
<p><strong>Around 30 GB/s</strong> – plenty for databases, caches (Redis/Valkey) and everything that keeps
many small objects in memory. RAM on this plan is, in our experience, limited more by
<strong>quantity</strong> (8 GB) than by throughput.</p>
<h3 id="step-4-nvme-disk">Step 4: NVMe disk</h3>
<p>Here the wheat separates from the chaff – the disk is the actual bottleneck for most
self-hosted apps. <code>fio</code> measures realistically when you bypass the page cache with
<code>--direct=1</code> (otherwise you measure RAM, not the disk). First the <strong>4K random IOPS</strong>
decisive for databases:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl"><span class="c1"># Read (4K random read)</span>
</span></span><span class="line"><span class="cl">fio --name<span class="o">=</span>rr --ioengine<span class="o">=</span>libaio --direct<span class="o">=</span><span class="m">1</span> --rw<span class="o">=</span>randread --bs<span class="o">=</span>4k <span class="se">\
</span></span></span><span class="line"><span class="cl">  --numjobs<span class="o">=</span><span class="m">4</span> --iodepth<span class="o">=</span><span class="m">32</span> --size<span class="o">=</span>512M --runtime<span class="o">=</span><span class="m">20</span> --time_based --group_reporting
</span></span><span class="line"><span class="cl">
</span></span><span class="line"><span class="cl"><span class="c1"># Write (4K random write) – same command, only --rw=randwrite</span>
</span></span><span class="line"><span class="cl">fio --name<span class="o">=</span>rw --ioengine<span class="o">=</span>libaio --direct<span class="o">=</span><span class="m">1</span> --rw<span class="o">=</span>randwrite --bs<span class="o">=</span>4k <span class="se">\
</span></span></span><span class="line"><span class="cl">  --numjobs<span class="o">=</span><span class="m">4</span> --iodepth<span class="o">=</span><span class="m">32</span> --size<span class="o">=</span>512M --runtime<span class="o">=</span><span class="m">20</span> --time_based --group_reporting</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">read:  IOPS=101k, BW=394MiB/s
</span></span><span class="line"><span class="cl">write: IOPS=67.0k, BW=262MiB/s</span></span></code></pre></div>
</div>
<p><strong>101,000 read and 67,000 write IOPS</strong> at 4K – that&rsquo;s real NVMe level and the reason why
Nextcloud, databases or Paperless feel noticeably smooth on this VPS. And the sequential
throughput (large files, backups, video):</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl"><span class="c1"># Read (sequential)</span>
</span></span><span class="line"><span class="cl">fio --name<span class="o">=</span>sr --ioengine<span class="o">=</span>libaio --direct<span class="o">=</span><span class="m">1</span> --rw<span class="o">=</span><span class="nb">read</span> --bs<span class="o">=</span>1M <span class="se">\
</span></span></span><span class="line"><span class="cl">  --numjobs<span class="o">=</span><span class="m">1</span> --iodepth<span class="o">=</span><span class="m">16</span> --size<span class="o">=</span>2G --runtime<span class="o">=</span><span class="m">15</span> --time_based
</span></span><span class="line"><span class="cl">
</span></span><span class="line"><span class="cl"><span class="c1"># Write (sequential) – same command, only --rw=write</span>
</span></span><span class="line"><span class="cl">fio --name<span class="o">=</span>sw --ioengine<span class="o">=</span>libaio --direct<span class="o">=</span><span class="m">1</span> --rw<span class="o">=</span>write --bs<span class="o">=</span>1M <span class="se">\
</span></span></span><span class="line"><span class="cl">  --numjobs<span class="o">=</span><span class="m">1</span> --iodepth<span class="o">=</span><span class="m">16</span> --size<span class="o">=</span>2G --runtime<span class="o">=</span><span class="m">15</span> --time_based</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">READ:  bw=4123MiB/s (4.3 GB/s)
</span></span><span class="line"><span class="cl">WRITE: bw=2937MiB/s (3.1 GB/s)</span></span></code></pre></div>
</div>
<p><strong>4.3 GB/s reading, 3.1 GB/s writing.</strong> A <code>restic</code> backup or a large <code>docker pull</code> is thus
done in seconds.</p>
<h3 id="step-5-network">Step 5: Network</h3>
<p>For throughput, you download a large test file from a well-connected server. We take the
Hetzner speed test in Falkenstein (Germany):</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">curl -o /dev/null -w <span class="s2">&#34;%{speed_download} B/s in %{time_total}s\n&#34;</span> <span class="se">\
</span></span></span><span class="line"><span class="cl">  https://fsn1-speed.hetzner.com/1GB.bin</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">246095181 B/s in 4.36s</span></span></code></pre></div>
</div>
<p><strong>~246 MB/s, i.e. about 2 Gbit/s</strong> – 1 GB in just over four seconds. A download from the US
(Ashburn) was, due to distance, at ~36 MB/s; within Europe the connection is excellent.
Finally the latency:</p>
<div class="sk-code">
  <span class="sk-code-head">Terminal</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">ping -c <span class="m">5</span> 1.1.1.1</span></span></code></pre></div>
</div>
<div class="sk-code">
  <span class="sk-code-head">Ausgabe</span>
  <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="cl">rtt min/avg/max/mdev = 12.314/12.337/12.365/0.019 ms</span></span></code></pre></div>
</div>
<p><strong>~12 ms</strong> to <code>1.1.1.1</code> (Cloudflare&rsquo;s Anycast resolver, i.e. a nearby network node – not a
purely German target), very consistent (the deviation is in the hundredths). IPv6 is active
and works; a ping over IPv6 was at ~26 ms.</p>
<h2 id="when-things-go-wrong">When things go wrong</h2>
<div class="troubleshoot not-prose">
<p><strong>Your figures are well below ours, especially for the CPU.</strong> A VPS shares the physical
CPU. Check the <strong>steal time</strong> (<code>vmstat 1</code>, column <code>st</code>) and <code>top</code> (line <code>%st</code>). If it&rsquo;s
persistently high, neighbors on the same host are computing right now. Measure again at a
different time of day – often the difference is gone then.</p>
<p><strong>The disk figures are absurdly high (e.g. &ldquo;10 GB/s random read&rdquo;).</strong> You&rsquo;re missing
<code>--direct=1</code> – then <code>fio</code> measures the RAM cache, not the NVMe. Always test with direct
I/O, otherwise the numbers are worthless.</p>
<p><strong><code>lsblk</code> shows <code>ROTA=1</code> (&ldquo;rotational&rdquo;) for <code>vda</code> in the column – is that a hard disk
instead of NVMe?</strong> No. That&rsquo;s a <strong>virtualization artifact</strong>: the virtio driver reports the
virtual disk as rotational across the board. The measured 100k+ IOPS and 4 GB/s prove that
real flash storage is behind it.</p>
<p><strong>The download is much slower than 2 Gbit/s.</strong> Measure against a <strong>nearby, fast</strong> server
(e.g. Falkenstein). A distant target or a slow counterpart limits the measurement, not your
VPS. A single <code>curl</code> stream also doesn&rsquo;t always exhaust the full bandwidth.</p>
<p><strong>Every run delivers different numbers.</strong> Normal – benchmarks fluctuate. Measure multiple
times, discard the first (&ldquo;warm&rdquo;) run and take the median. Also compare only <strong>the same
tool versions and parameters</strong> with each other.</p>

</div>

<h2 id="keeping-an-eye-on-performance">Keeping an eye on performance</h2>
<ul>
<li><strong>Who is the VPS 1000 G12 enough for?</strong> For practically all the single services on this
site – SSH, <a href="/en/tutorials/traefik-reverse-proxy/">Traefik</a>, Vaultwarden, Uptime Kuma, a
small Nextcloud. It gets tight less at CPU or disk than at <strong>RAM</strong>: as soon as several
heavy apps (Nextcloud + Immich + databases) run in parallel, an upgrade to the
<a href="/en/netcup-recommendation/">VPS 2000</a> (16 GB) is the most sensible next step.</li>
<li><strong>Watch steal time long-term.</strong> A one-off benchmark is a momentary snapshot. Whoever
wants to keep an eye on performance long-term takes CPU steal, I/O and network into a
<a href="/en/tutorials/monitoring-grafana-prometheus/">Grafana dashboard</a> – there you see
creeping degradation before it hurts.</li>
<li><strong>Re-measure after changes.</strong> A server migration, a product switch or a new netcup
generation changes the figures. Keep your benchmark outputs (a simple text file in the
backup is enough), then you have a basis for comparison.</li>
<li><strong>Stay honest:</strong> benchmark numbers age and fluctuate. They&rsquo;re an orientation, not a
promise – the shared vCores mean the real performance always also depends on the
neighbors on the host. For the entry-level price, though, the VPS 1000 G12 delivers a
remarkably well-rounded performance.</li>
</ul>
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