SKU: 20139151476

High Lifter Portal Gear Lift 6'' RZR TURBO (2 & 4 Seater) - 45% Single Idler Version

$1662.75 $1847.50
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Ships within 48 hours · Estimated delivery Aug 6 - Aug 11

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Description

High Lifter Portal Gear Lift 6'' RZR TURBO (2 & 4 Seater) - 45% Single Idler VersionFree shipping in the lower 48 states. SKU: PGL 645 RZRT Want lift plus power and performance? High Lifter engineered a gearing setup for a 6'' portal with 45% gear reduction. You can run a larger tire size between a 33 to 39 inches and have the torque and horsepower you need. The 45% gear reduction is a robust set of portals giving height and power in any terrain. Mud Riding geared to get you out of the thickest mud holes and 6 inches of height to

Free shipping in the lower 48 states.

SKU: PGL-645-RZRT

Want lift plus power and performance? High Lifter engineered a gearing setup for a 6'' portal with 45% gear reduction. You can run a larger tire size between a 33 to 39 inches and have the torque and horsepower you need. The 45% gear reduction is a robust set of portals giving height and power in any terrain. Mud Riding geared to get you out of the thickest mud holes and 6 inches of height to pass over anything that comes in your way. Rock Climbing 45% gear reduction makes that rocky terrain seem easy. You’ll have the power to ease right over rocks and boulders, plus added lift to run big tires to go places your friends can’t.

Installation Instructions

Why is this 6” kit better than our competitor?

Forged Gear Boxes

  • Strongest boxes on the market because forging produces a tougher piece of metal
  • Forging is stronger than both cast and billet aluminum
  • Competitors use cast aluminum and billet aluminum boxes
  • These portal boxes are extremely robust and give you more worry-free miles than any other portal

Gear Box Venting

  • Customers asked for box venting and we give you the option
  • Our box design offers a plug for venting with an optional easy to install kit that will be available soon
  • Vent kits allow an advantage of cooling which reduces early deterioration of the gaskets and seals

Gasket Material and Design

  • High density Kevlar fiber gaskets plus no additional sealant is needed
  • Gasket material is creep resistant plus oil and coolant resistant

Seals

  • Two oil seals on the spindle shaft for 100% more sealing area
  • Dual seals prevent water intrusion and oil leaks
  • True triple seal on the input shaft which includes a wiper seal that provides a significant extra layer of protection

Backing Plate

  • These are the strongest backing plates on the market
  • 5/16” steel plate with Bent flanges for strength and durability
  • Welded gusset brackets and designed to factory off-set
  • Works with all control arms that are built to factory hub specifications

13” Rotor

  • Precision ground stainless steel rotors (this is a big deal for brake performance)
  • Access holes for ease of assembly and disassembly
  • Slotted rotor allows for heat dissipation and cooling

Gear Profile

  • Alloy steel heat treating process increases overall internal and external strength
  • CNC precision ground machining ensures excellent fitment and increased strength
  • Controlled gear lapping for ease of installation and a quieter performance

                  Fits:

                  2016 Polaris RZR TURBO XP EPS
                  2016 Polaris RZR TURBO 4 XP EPS
                  2017 Polaris RZR TURBO XP EPS
                  2017 Polaris RZR TURBO 4 XP EPS
                  2018 Polaris RZR TURBO XP DYNAMIX Edition
                  2018 Polaris RZR TURBO XP EPS
                  2018 Polaris RZR TURBO XP 4 EPS
                  2018 Polaris RZR TURBO XP FOX Edition
                  2018 Polaris RZR TURBO XP 4 FOX Edition
                  2019 Polaris RZR TURBO XP EPS
                  2019 Polaris RZR TURBO XP LE
                  2019 Polaris RZR TURBO XP DYNAMIX Edition
                  2019 Polaris RZR TURBO XP 4 EPS
                  2019 Polaris RZR TURBO XP 4 LE
                  2019 Polaris RZR TURBO XP 4 DYNAMIX Edition
                  2020 Polaris RZR TURBO XP
                  2020 Polaris RZR TURBO XP 4
                  2021 Polaris RZR Turbo XP
                  2021 Polaris RZR Turbo XP 4

                  Click here for High Lifter's limited lifetime warranty.

                  SS | 1-7-22

                  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]
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                  SKU: 20139151476

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                  4.7 ★★★★★
                  Based on 28 reviews
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                  Product Reviews
                  O
                  Om S
                  Fort Morgan, 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
                  San Leandro, 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
                  Chelsea, 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
                  Fort Morgan, 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
                  Fort Morgan, 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

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