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Description
BM Performance Wheel Spacer Set | LK 120/5 NLB 72.6 | 18mmMade for BM Performance by one of Germany's largest manufacturer of wheel spacer and adaptor systems. With the wheel spacers installed, your car will both look and perform better than it ever has before. PRODUCT INFORMATION BM Performance WHEEL SPACERS The BMPC System 5 non hub centric wheel spacers are designed for optimum driving behavior and safety. The rim is centered using the vehicle hub. Extended wheel bolts are additionally required. Spacer
Made for BM Performance by one of Germany's largest manufacturer of wheel spacer and adaptor systems. With the wheel spacers installed, your car will both look and perform better than it ever has before.
PRODUCT INFORMATION
BM Performance WHEEL SPACERS
The BMPC System 5 non-hub centric wheel spacers are designed for optimum driving behavior and safety. The rim is centered using the vehicle hub. Extended wheel bolts are additionally required.
Spacer Size 18mm (36mm Per Axle) Bolt Pattern5 x 120mm Centre Bore72.6mm ColourBlack Anodized Contents2 Spacers (1 Axle) Per Kit
Features
High strength, light weight aluminum/ magnesium alloy.
Precision CNC machined.
Includes detailed mounting instructions for quick and easy installation.
Delivered with TUV or ABE approval.
Engineered, manufactured and tested in Germany.
WHEEL MOUNTING INFORMATION
This spacer set is suitable for use on the following vehicles in combination with the applicable size wheel bolts.
Wheel Bolt M12x1.5mm
Suitable for most BMW models (E-Series) built until 2012.
Length28mm Head Size17mm Head ShapeCone 60° ColourBlack Set Quantity10 Wheel Bolts
Suitable Models
E82, E87 & E88 1 Series including 1 Series M (1M)
E36 3 Series including M3
E46 3 Series including M3
E90, E91, E92 & E93 3 Series including M3
E60 & E61 5 Series including M5
E63 & E64 6 Series including M6
E38 7 Series
E31 8 Series
E84 X1
E36/7/8 Z3 including Z3M
E85 & E86 Z4 including Z4M
E89 Z4
E52 Z8
Wheel Bolt M14x1.25mm
Suitable for most BMW models (F-Series and G-Series) built after 2012.
Length30mm Head Size17mm Head ShapeCone 60° ColourBlack or Silver Set Quantity10 Wheel Bolts
Suitable Models
F20 1 Series
F22 & F23 2 Series
F87 M2, M2 Competiton and M2 CS
F30, F31 & F34 3 Series
F80 M3 and M3 CS
F32, F33 & F36 4 Series
F82 & F83 M4, M4 CS and M4 GTS
F07, F10 & F11 5 Series including M5
F06, F12 & F13 6 Series including M6
F01 & F02 7 Series
F25 X3
F26 X4
E70 X5M (This spacer kit is suitable for the rear only)
E71 X6 & X6M (This spacer kit is suitable for the rear only)
Mini R60 Countryman
Mini R61 Paceman
Wheel Bolt M14x1.5mm
Suitable for select BMW models (E-Series) until 2012.
Length33mm Head Size17mm Head ShapeCone 60° ColourBlack or Silver Set Quantity10 Wheel Bolts
Suitable Models
E65 & E66 7 Series
E83 X3
E53 X5
Note:Fitment may not be possible on certain rim or hub types due to the low wheel spacer thickness. Modifications or larger spacers may be required. Please contact us if you have any questions.
Models
1 Series / E82 / E88 (2007-2013) / 1 Series M (1M)
This is a great resource when building systems that integrate with AI. It manages to cover the entire lifecycle and even tips for corporate environments!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 26, 2025
O
Om S
Waukegan, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon.
The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice.
Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening.
Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development.
Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Birmingham, US
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity.
What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike.
Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
N
Nader
Houston, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them.
Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!)
Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples).
Seems like the book was rushed, and the author has limited hands on experience (if any).
At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Port Orchard, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket!
Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC.
- How to prepare your data for training by making it extremely clean.
Developing the brains: the practical aspects of training, optimizing, and maintaining your models.
- Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities.
Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise.
- It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!)
Really, this feels like a useful toolkit, so Ken thank you for that resource
Thanks, Idan Habler
,
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