SKU: 61499122045

High Lifter Portal Gear Lift 4'' 2021 Ranger 1000 (Standard Cab & Crew Models) - 15% Dual Idler

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

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For Your Every Summer RSVP, with Code: SUMMER15

Description

High Lifter Portal Gear Lift 4'' 2021 Ranger 1000 (Standard Cab & Crew Models) - 15% Dual IdlerFree shipping in the lower 48 states. SKU: PGL 415DI RNG1 2 This High Lifter 4'' Portal Gear Lift is made tough and ready for any challenge. Now engineered with a gearing setup that allows two idler gears in the portal box to spread the load between twice as many teeth on the gears. This doubles the area and reduces the stress by half, allowing more abuse. This kit is for riders who are looking for torque and power. High Lifter Portal Gear Lift (Each

Free shipping in the lower 48 states.

SKU: PGL-415DI-RNG1-2

This High Lifter 4'' Portal Gear Lift is made tough and ready for any challenge. Now engineered with a gearing setup that allows two idler gears in the portal box to spread the load between twice as many teeth on the gears. This doubles the area and reduces the stress by half, allowing more abuse. This kit is for riders who are looking for torque and power.

High Lifter Portal Gear Lift (Each kit includes 4 portal boxes)

15% & 30% Dual Idler Reductions

What does the Dual Idler Gear Lift offer?

  • High Lifter improved the portal design by adding a second idler gear in the gear box
  • The dual idler gears spread the load over twice as many teeth on the gear sets, which doubles the area and reduces stress by half.
  • You gain more reliable torque transfer
  • Stop burning up belts and breaking so many axles; differentials; drive shafts; snorkel gears…
  • Gear reduction extends brake life by needing brakes less often due to greatly improved engine braking
  • Even though a lower gear ratio will get your speedometer closer to a stock reading, that is still too high a gear to offset the loss of torque caused by the larger tires. If you don’t have a need to run fast, a lower ratio performs better and give you the power you want!

Why is this 4” 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

Rotors

  • 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

Tire Fitment:
Largest Tire with Portal: 33"
Largest Tire with Forward Arms: 35"
Our stated tire fitment guide is a general fitment and is in no way guaranteed. Tires and lifts vary by manufacture and tire fitment can be affected by other modifications. Always verify your brand of tires, lift, and other modifications prior to making a buying decision.

Wheel Requirements:
14" or larger
14" factory wheels must run 1" spacer
14" & 15" can not exceed 4-1/2" backspacing
16" & larger can not exceed 5" backspacing

            Fits:

            2021 Polaris Ranger 1000
            2021 Polaris Ranger 1000 EPS
            2021 Polaris Ranger 1000 Premium
            2021 Polaris Ranger 1000 Crew
            2021 Polaris Ranger 1000 Crew Premium
            2021 Polaris Ranger 1000 XP Premium
            2021 Polaris Ranger 1000 XP Crew Premium

            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]
            • Please click here for more details>>> Return & Exchange Policy
            SKU: 61499122045

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            4.2 ★★★★★
            Based on 25 reviews
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            Product Reviews
            O
            Om S
            Boise, 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
            Lake Worth, 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
            West Palm Beach, 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
            Lexington, 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
            Los Angeles, 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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