SKU: 50616123998

QA1 GM Pro Front Coil-Over System - MOD Series - 10in x 650lbs/in - Flat Large - Aluminum

$1124.55 $1249.50
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Description

QA1 GM Pro Front Coil-Over System - MOD Series - 10in x 650lbs/in - Flat Large - Aluminumsoft or firm compression and rebound valve packs also available. Once the desired valving is in place, the unique double adjustable design, with adjustable low speed bleed, allows for fully independent control over the compression and rebound characteristics. With all these adjustability options, the MOD Series shock achieves an expansive force curve capability and an unprecedented level of tunability. The shock also features mounting adjustability to

soft or firm compression and rebound valve packs also available. Once the desired valving is in place, the unique double adjustable design, with adjustable low-speed bleed, allows for fully independent control over the compression and rebound characteristics. With all these adjustability options, the MOD Series shock achieves an expansive force curve capability and an unprecedented level of tunability. The shock also features mounting adjustability to accommodate a variety of vehicles and mounting configurations. The nitrogen-charged canister is available in a piggyback or remote configuration for ease of installation in tight areas, and the base eyelet is indexable, so you can unbolt it and reattach it at the angle you need for the best shock and canister placement. Like all QA1 shocks, the MOD Series shock is 100% dyno tested and serialized and proudly made in QA1's Lakeville, Minnesota facility.

  • Valve packs shock can quickly and easily be revalved without interrupting the oil path or opening the shock up for debris and air contamination
  • QuickTune Technology: dry modular valve packs that can easily be swapped out
  • Remote or piggyback canister mounting options
  • 4-way adjustable high and low speed bleed
  • 100% dyno tested and serialized
  • Made in the USA

This Part Fits:

Year Make Model Submodel
1958-1975 Chevrolet Bel Air Base
1958-1972 Chevrolet Biscayne Base
1960 Chevrolet Biscayne Fleetmaster
1966-1972,1986-1991 Chevrolet Caprice Base
1973-1991 Chevrolet Caprice Classic
1986-1990 Chevrolet Caprice Classic Brougham
1976-1978,1981-1982 Chevrolet Caprice Classic Estate
1976-1981 Chevrolet Caprice Classic Landau
1987-1990 Chevrolet Caprice Classic LS Brougham
1991 Chevrolet Caprice Classic LTZ
1975-1976,1979-1980 Chevrolet Caprice Classic Sport
1973-1974 Chevrolet Caprice Estate
1975 Chevrolet Caprice Estate Wagon
1958 Chevrolet Del Ray Base
1971-1985 Chevrolet Impala Base
1975-1977 Chevrolet Impala Custom
1976 Chevrolet Impala Custom Landau
1981-1982 Chevrolet Impala Estate
1977-1979 Chevrolet Impala Landau
1976 Chevrolet Impala S
1975-1976,1979-1980 Chevrolet Impala Sport
1994-1996 Chevrolet Impala SS
1960 Edsel Ranger Base
1960-1964 Ford Galaxie Base
1961 Ford Galaxie Club Victoria
1960 Ford Galaxie Special
1961 Ford Galaxie Starliner
1961 Ford Galaxie Sunliner
1961 Ford Galaxie Town Victoria
1960,1963 Mercury Country Cruiser Base
1963-1964 Mercury Marauder Base
1961 Mercury Meteor 600
1961-1963 Mercury Meteor Base
1962-1963 Mercury Meteor Custom
1962-1963 Mercury Meteor S-33
1960-1964 Mercury Monterey Base
1962-1963 Mercury Monterey Custom
1962 Mercury Monterey Custom S-55
1963 Mercury Monterey S-55
Shipping Notes
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Exchange/Return Notes
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  • Final sale items are not eligible for returns or exchanges.
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SKU: 50616123998

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4.8 ★★★★★
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A
Allen Wyma
Boise, US
★★★★★ 5
Great Resource when Integrating AI
Format: Kindle
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
Natrona Heights, 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
Omaha, 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
Charlottesville, 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
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Reviewed in the United States on December 31, 2025
N
noam barkay
Lowell, 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

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