SKU: 3504502755

Bilstein B6 2009 GMC Sierra 2500 HD SLE Rear 46mm Monotube Shock Absorber

$82.80 $92.00
Save 10%
No.2 Bestseller on salfueradeti.es >

Pay in installments of $23.00 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Aug 27 - Sep 1

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Bilstein B6 2009 GMC Sierra 2500 HD SLE Rear 46mm Monotube Shock AbsorberBilstein B6 4600 shock absorbers are designed as a direct fit upgrade to OE shock absorbers on stock height light trucks and SUVs. These shock absorbers feature a monotube design which provides consistent fade free performance. B6 4600 shock absorbers utilize a unique, velocity sensitive, digressive piston which reacts to changing road conditions. All B6 4600 shock absorbers are tuned for each specific application to ensure optimal performance is

Bilstein B6 4600 shock absorbers are designed as a direct fit upgrade to OE shock absorbers on stock height light trucks and SUV’s. These shock absorbers feature a monotube design which provides consistent fade free performance. B6 4600 shock absorbers utilize a unique, velocity sensitive, digressive piston which reacts to changing road conditions. All B6 4600 shock absorbers are tuned for each specific application to ensure optimal performance is achieved. B6 4600 shock absorbers offer a significant improvement in ride quality, handling, and comfort.

Installation Instructions
Warranty
Material Safety Data Sheet
Material Safety Data Sheet
Installation Instructions
Warranty
Catalog

This Part Fits:

Year Make Model Submodel
2005 Chevrolet Silverado 1500 HD Base
2001-2003,2005 Chevrolet Silverado 1500 HD LS
2001-2003,2005-2006 Chevrolet Silverado 1500 HD LT
2007 Chevrolet Silverado 1500 HD Classic LT
1999-2004 Chevrolet Silverado 2500 Base
1999-2004 Chevrolet Silverado 2500 LS
1999-2004 Chevrolet Silverado 2500 LT
2004 Chevrolet Silverado 2500 WT
2001-2005 Chevrolet Silverado 2500 HD Base
2001-2006 Chevrolet Silverado 2500 HD LS
2001-2010 Chevrolet Silverado 2500 HD LT
2007-2010 Chevrolet Silverado 2500 HD LTZ
2003-2010 Chevrolet Silverado 2500 HD WT
2007 Chevrolet Silverado 2500 HD Classic LS
2007 Chevrolet Silverado 2500 HD Classic LT
2007 Chevrolet Silverado 2500 HD Classic WT
2001-2003,2005-2006 GMC Sierra 1500 HD SLE
2001-2003,2005-2006 GMC Sierra 1500 HD SLT
2007 GMC Sierra 1500 HD Classic SLE
2007 GMC Sierra 1500 HD Classic SLT
2002-2004 GMC Sierra 2500 Base
1999-2002 GMC Sierra 2500 SL
1999-2004 GMC Sierra 2500 SLE
1999-2004 GMC Sierra 2500 SLT
2003-2004 GMC Sierra 2500 WT
2002-2005 GMC Sierra 2500 HD Base
2001-2002,2006 GMC Sierra 2500 HD SL
2001-2010 GMC Sierra 2500 HD SLE
2001-2010 GMC Sierra 2500 HD SLT
2003-2010 GMC Sierra 2500 HD WT
2007 GMC Sierra 2500 HD Classic SL
2007 GMC Sierra 2500 HD Classic SLE
2007 GMC Sierra 2500 HD Classic SLT
2007 GMC Sierra 2500 HD Classic WT
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: 3504502755

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.2 ★★★★★
Based on 10 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
N
Nader
Draper, 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
New York, 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
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
Whiting, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025
V
Vineeth Sai
Draper, US
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
C
Verified Purchase
CL
Lexington, US
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 14, 2025

recommand products

AMAZON YooGun Fridge Organizers and Storage Bins, 8 Set
26.99
Shockwave Lab SL-127 SL127 Light Upgrade Kit for Titan Class Metroplex Upgrade Kit
22.99
Monopoly: Leamington Spa
26.95
Missguided green sports originals graphic oversized sweatshirt
25.00
Abeka World Histoy and Cultures 3rd Ed LOT of 3
23.59