SKU: 59010076954

KEF REFERENCE 2 META COMPACT 3-WAY CENTRE SPEAKER

$4500.00 $5000.00
Save 10%
No.2 Bestseller on salfueradeti.es >

Pay in installments of $1250.00 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 24 - Jul 29

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

KEF REFERENCE 2 META COMPACT 3-WAY CENTRE SPEAKERThe benchmark of centre speakers, condensed Featuring 12th generation Uni Q driver array with MAT, Reference 2 Meta centre speaker (can be used as Left Centre Right speaker) has the uncanny ability to completely immerse you in both music and movies. Designed for people with smaller rooms but demand full scale, high performance sound, Reference 2 Meta delivers on both fronts. The benchmark of benchmarks Since 1973, The Reference has continually set the

 

The benchmark of centre speakers, condensed

Featuring 12th generation Uni-Q® driver array with MAT™, Reference 2 Meta centre speaker (can be used as Left-Centre-Right speaker) has the uncanny ability to completely immerse you in both music and movies. Designed for people with smaller rooms but demand full-scale, high-performance sound, Reference 2 Meta delivers on both fronts.



The benchmark of benchmarks

Since 1973, The Reference has continually set the benchmark for loudspeakers and sound reproduction. Pioneering the use of digital technologies to achieve the highest audio accuracy, every pair can be matched within 0.5dB to the laboratory-maintained reference standard.



Always innovating

Since the first Reference speaker, KEF engineers have continued to innovate using what is possible with The Reference. Ground-breaking in its first incarnation, each subsequent iteration of The Reference has added to the world’s knowledge of the science of acoustics.



Designed, engineered and handcrafted in UK

Since 1961, we have been creating remarkable award-winning loudspeakers at our UK home in Maidstone, Kent. As our flagship HiFi speakers, The Reference is still being designed, engineered, and handcrafted in Maidstone today.



 

SPECIFICATIONS

Design
Three-way bass reflex

Drive units
Uni-Q driver array:
HF: 25 mm (1 in.) aluminium dome with MAT
MF: 125 mm (5 in.) aluminium cone

Bass units:
LF: 2 x 165 mm (6.5 in.) aluminium cone
Frequency range free field (-6dB)
65Hz - 45kHz

Frequency range typical in room bass response (-6dB)
46Hz

Frequency response (±3dB)
80Hz – 35kHz

Crossover frequency
450 Hz, 2.1 kHz

Amplifier requirements
50 - 300W

Sensitivity (2.83V/1m) 
86dB

Harmonic distortion 2nd & 3rd harmonics (90dB, 1m)
<0.5% 40Hz – 100kHz
<0.2% 200Hz – 2kHz
<0.1% 2kHz - 20kHz

Maximum output (peak sound pressure level at 1m with pink noise)
113.5dB

Impedance
4 Ω (min. 3.2 Ω)

Weight
22.8 kg (50.3 lbs.)

Dimensions (H x W x D)(with grille and terminal)
205 x 630 x 335 mm(8.1 x 24.8 x 13.2 in.)
Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 59010076954

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.8 ★★★★★
Based on 19 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
S
Verified Purchase
Shannon
Charlottesville, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Fort Morgan, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Omaha, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Lake Worth, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Alexandria, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

recommand products

Kingston Brass Cc3098 Tub Drain, Brushed Nickel
235.61
TEKNIA WHITE SILVER MASK
23.17
SENSIBIO H2O MICELLAR WATER
20.00
Kingston Brass Abt1010-1 Vintage Cradle, Polished Chrome
77.35
Kingston Brass Ba6013Orb Millennium 24 Dual Towel Bar, Oil Rubbed Bronze
88.75