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Data analysis — HeatpumpMonitor.org

Does brand matter?
What 600+ real heat pumps actually tell us

Vaillant vs Mitsubishi vs Samsung vs Daikin — the question every buyer asks and the one manufacturers least want answered with real data. We went to the only dataset that can answer it honestly.

639 systems Real metered data Nov 2024 – Nov 2025 Source: HeatpumpMonitor.org / OpenEnergyMonitor
3.86
avg SPF H4 — 170 air source systems, no cooling
2.0×
SPF range within a single brand — typical spread
R²=0.55
correlation: flow temperature vs performance
~0
additional explained variance from brand alone

The question everyone asks

Walk into any heat pump forum, online community, or installer conversation and within minutes someone asks: which brand should I choose? Vaillant or Mitsubishi? Samsung or Daikin? Is it worth paying the premium for a Viessmann? The question is entirely reasonable — for a £10,000–20,000 purchase that will heat your home for 15–20 years, brand reputation feels like it should matter enormously.

The problem is that almost all the comparison content available is manufacturer-funded marketing, installer preference, or anecdotal forum opinion. HeatpumpMonitor.org is the only publicly available UK dataset with enough systems, enough brands, and enough measurement rigour to actually answer the question with data.

// About the dataset

639 heat pump systems uploading continuous monitoring data as of November 2025, including 448 with full MID-certified metering (billing-grade heat meters and electricity meters). The analysis below focuses on 170 air source systems at the H4 boundary with no summer cooling, achieving a dataset average SPF H4 of 3.86. Systems span the full range of UK property types, installer quality, and commissioning approaches. The dataset includes systems installed by some of the best heat pump engineers in the UK — meaning it captures what good performance looks like, not just average.

The short answer

Brand matters less than you think.
System design, flow temperature, and commissioning matter far more.

The data is unambiguous on this point. When you look across the full dataset, the strongest single predictor of annual performance (R² = 0.55) is not the brand name on the outdoor unit — it is the weighted average flow temperature minus outside temperature. Physics, not marketing. The lower the flow temperature relative to outside conditions, the higher the SPF. Every manufacturer's unit obeys this rule because it's thermodynamic law, not engineering preference.

What the equations actually say

The HeatpumpMonitor.org team have published the regression equations directly from the dataset. These are worth knowing because they tell you exactly what a flow temperature decision is worth in pounds per year.

Equation 1: SPF H4 vs weighted average flow temperature
SPF H4 = −0.1008 × flow_temp + 7.4189
90% prediction interval: ± 0.55  |  R² = 0.515

Reading the equation directly:

Weighted avg flow temp Typical SPF H4 ±90% interval Assessment
30°C 4.4 ±0.55 Excellent — well-optimised system
35°C 3.9 ±0.55 Good — well-tuned radiator system
40°C 3.4 ±0.55 Moderate — room for improvement
45°C 2.9 ±0.55 Poor — likely sub-optimal commissioning

Every 5°C reduction in average flow temperature adds approximately 0.5 to the annual SPF. On a typical UK home using 15,000 kWh of heat per year, the difference between SPF 2.9 and SPF 4.4 is the difference between consuming 5,172 kWh of electricity and 3,409 kWh — a saving of 1,763 kWh annually, worth approximately £489 at 27.75p/kWh. That's every year, for the life of the system.

What brand actually explains: the Carnot percentage

Once you control for flow temperature and outside conditions, what's left? The HeatpumpMonitor.org team measure this using the practical efficiency factor — the percentage of the theoretical ideal (Carnot) COP each system actually achieves. This is where any brand-level quality difference would show up.

Carnot COP formula
Carnot_COP = (T_condensing + 273) / ((T_condensing + 273) − (T_evaporating + 273))

Practical_COP = % Carnot × Carnot_COP
// Industry assumption: ~50% of ideal. Reality: 45–58% depending on system.

The impact of this percentage is substantial even in a narrow range. At the same system temperatures — 35°C flow, 6°C outside — the difference between operating at 45% and 55% of ideal Carnot COP:

% Carnot Ideal COP Practical COP Annual electricity cost*
40% 8.4 3.35 £1,118
45% 8.4 3.77 £993
50% 8.4 4.19 £894
55% 8.4 4.61 £812

* Based on 15,000 kWh annual heat demand at 27.75p/kWh electricity. Conditions: 35°C flow, 6°C outside.

A £306/year difference between 40% and 55% Carnot. That's real. The question is whether it's explained by brand — and the answer from the data is: only partially, and less than you'd expect.

Carnot percentage ranges by brand — what the data shows

The HeatpumpMonitor.org team have published the % Carnot ranges they observe for each major brand across their dataset. The results are striking for what they reveal about within-brand variation:

Viessmann
45% — 58%
13-point range within brand
Vaillant
41% — 54%
13-point range within brand
Samsung
41% — 50%
9-point range within brand
Mitsubishi
39% — 56%
17-point range within brand

Every brand has a substantial spread within it. Mitsubishi's best-performing systems achieve 56% Carnot; its worst achieve 39% — a 17-point spread within a single manufacturer's products. The variation between the worst Mitsubishi system and the best Viessmann system is only slightly larger than the variation within Mitsubishi alone.

The clear implication: choosing Viessmann over Mitsubishi, or Vaillant over Samsung, does not guarantee you the upper end of the Carnot range. A poorly commissioned Vaillant will underperform a well-commissioned Mitsubishi. The brand badge is a starting condition, not an outcome guarantee.

What actually explains the within-brand variation

If not brand, what causes a Mitsubishi system to achieve 56% Carnot in one installation and 39% in another? The OpenEnergyMonitor team have investigated this carefully and identified several contributing factors:

Factor Impact Fixable?
Primary pipework length before heat meter High — can drop COP from 4 to 3 At design stage
Sub-optimal weather compensation settings High — drives unnecessarily high flow temps ✓ Yes — at commissioning
Rapid cycling in mild weather Moderate — never reaches efficient regime ✓ Yes — settings/sizing
Heat meter inaccuracies (sensor placement) Low-moderate — MPE up to 7% Partially at install
Buffer tanks, low loss headers, PHEs Variable — poor balancing can hurt ✓ Yes — design stage
Compressor operating speed (high RPS vs low) Significant — same unit, 3.3 vs 4.6 COP ✓ Yes — sizing/settings
Refrigerant charge / manufacturing defects Low but real — undercharged systems Warranty/service

The most striking item on this list is compressor operating speed. Analysis of the Vaillant performance tables published on HeatpumpMonitor.org shows the same 5 kW unit achieving a COP of 4.6 at 40 rps and only 3.3 at 110 rps — at identical system temperatures. A heat pump delivering most of its heat at high compressor speed (because it's oversized, or weather compensation is set too aggressively) will consistently underperform the same unit running at lower speed — regardless of brand.

The commissioning gap: the UK's biggest heat pump problem

The most important comparison in the dataset isn't between brands — it's between HeatpumpMonitor.org's average SPF of 3.86 and the Electrification of Heat (EoH) trial's average SPF of 2.81. Both datasets cover real UK homes. Both cover real heat pumps. The difference is 1.05 SPF points — enormous in financial terms.

// The EoH vs HeatpumpMonitor.org gap

A peer-reviewed study published in November 2025 (Energy and Buildings, Elsevier) draws on both datasets to explain the gap. Its conclusion: "high efficiency is closely linked to operation at low flow temperatures... the study highlights several key factors including suboptimal weather-compensation settings that drive unnecessarily high flow temperatures, frequent cycling on room temperature, and extended operation at less efficient compressor modulation levels."

The EoH trial covered 165 Vaillant Arotherm+ systems. The OpenEnergyMonitor team inspected every single one manually and categorised the weather compensation quality as Good, OK, or Bad. The result: a significant proportion had sub-optimal weather compensation — running at higher flow temperatures than necessary, reducing their SPF by approximately 0.5–1.0 points compared to equivalently-sized and installed systems on HeatpumpMonitor.org with properly tuned settings.

This is the Vaillant aroTHERM+ — one of the most popular heat pumps in the UK, installed under a major government programme. The problem wasn't the hardware. It was the commissioning.

On a typical UK home with 15,000 kWh annual heat demand, the difference between SPF 2.81 (EoH average) and SPF 3.86 (HeatpumpMonitor.org average) is approximately 1,400 kWh of electricity per year — worth about £388 at the standard rate. Over 15 years of ownership that's £5,820 in wasted electricity. From systems that are largely the same hardware as the high performers.

What good looks like: the case study systems

The dataset includes individually published case studies at the high end. Three examples from the documentation are instructive:

System Heat pump SPF H4 Coldest day flow temp Design flow temp
System 68 10 kW Viessmann 5.0 33°C avg (36°C max) 40°C
System 278 10 kW Vaillant 4.8 33°C avg (35.5°C max) 43°C
System 53 5 kW Vaillant 4.5 31.3°C avg (36°C max) 35°C

These high-performing systems have one thing in common: they all run well below their design flow temperature even on the coldest days. System 68 was designed for 40°C and ran at 33°C. System 278 was designed for 43°C and ran at 33°C. This is the practical efficiency factor in action — flow temperatures well below design indicate that real-world heat loss is lower than the survey calculation predicted, and that the weather compensation has been tuned to reflect actual demand.

The brand question: a proper answer

Having looked at all the data, here is the most honest answer the dataset can provide to "which brand should I buy?":

Approximate Carnot % range — same brand, different installs
Viessmann
45–58%
Vaillant
41–54%
Mitsubishi
39–56%
Samsung
41–50%

Each bar shows the observed range within that brand on HeatpumpMonitor.org. The overlap between brands is large. The within-brand variation is substantial.

The brand ranges overlap heavily. A well-commissioned Mitsubishi easily outperforms a poorly commissioned Vaillant. A well-commissioned Samsung can match the mid-range Viessmann performance. The top of the Vaillant range is close to the top of the Viessmann range.

This does not mean brand is irrelevant. Some legitimate brand-level considerations remain:

Consideration What the data says
Installer familiarity An installer who knows a specific brand's commissioning interface thoroughly is more likely to tune it optimally. This is arguably the most important brand-adjacent consideration.
Controls and app quality Vaillant's myVaillant and integration with third-party optimisers is currently leading. Better controls make proper weather compensation more accessible.
Modulation range Some models modulate down further than others in mild weather, reducing cycling. This affects the low-end of the Carnot range more than the high-end.
R290 refrigerant Vaillant and some others have moved to natural refrigerant R290 (propane, GWP=3). R32 units (Samsung, Daikin, Mitsubishi) are still widely installed. Environmental consideration, not performance.
Installer network depth Vaillant, Mitsubishi, and Daikin have the deepest UK installer networks. More installers means more competition and easier servicing long-term.

What to actually ask when buying a heat pump

The HeatpumpMonitor.org data answers the brand question definitively: system design and commissioning dominate performance. Brand is secondary. Armed with that, here are the questions that actually matter:

The data from HeatpumpMonitor.org is publicly accessible at heatpumpmonitor.org. You can filter by brand, view individual system performance, and compare your prospective heat pump model against real-world results before you sign anything.

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