SKU: 71488128227

MMI Door 64 in. x 80 in. Left-Hand Inswing Classic 6-Panel Primed Steel Prehung Front Door with Brickmould

$682.27 $758.08
Save 10%
No.2 Bestseller on salfueradeti.es >

Pay in installments of $189.52 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Aug 6 - Aug 11

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

MMI Door 64 in. x 80 in. Left-Hand Inswing Classic 6-Panel Primed Steel Prehung Front Door with BrickmouldMMI Door 64 in. x 80 in. Left Hand Inswing Classic 6 Panel Primed Steel Prehung Front Door with Brickmould Introducing the MMI Door Classic 6 Panel Front Door, a perfect blend of style, durability, and security. This prehung door, featuring a timeless 6 panel design and brickmould, ensures easy installation and a sophisticated look for your home. Crafted from high quality primed steel, this door is built to withstand the elements and provide long

MMI Door 64 in. x 80 in. Left-Hand Inswing Classic 6-Panel Primed Steel Prehung Front Door with Brickmould

Introducing the MMI Door Classic 6-Panel Front Door, a perfect blend of style, durability, and security. This prehung door, featuring a timeless 6-panel design and brickmould, ensures easy installation and a sophisticated look for your home. Crafted from high-quality primed steel, this door is built to withstand the elements and provide long-lasting performance. The left-hand inswing design offers added security and convenience.

Key Features:

  • Durable Construction: Made from 24-gauge galvanized steel with 22-gauge steel stiles and rails for enhanced strength and security.
  • Energy Efficient: Features a one-piece, high-density polystyrene core for excellent insulation, meeting or exceeding current energy code standards.
  • Easy Installation: Prehung on a 6-9/16 inch primed FrameSaver frame with matching brickmould attached.
  • Classic Design: Timeless 6-panel design, ready to be painted to match your home’s aesthetic.
  • Comprehensive Warranty: Includes a 10-year warranty on the door component and a limited lifetime warranty on the prehung MSystem.

Please check the Product Installation Guide Here

Specifications:

Dimension Measurement
Door Height 81.75 in
Door Thickness 1.75 in
Door Width 66 in
Jamb Size 6-9/16 in
Nominal Door Height 80 in
Nominal Door Thickness 2 in
Nominal Door Width 64 in
Rough Opening Height 82.25 in
Rough Opening Width 66.5 in

Details:

  • Bore Type: Double Bore
  • Color Family: Off White
  • Color/Finish: Primed
  • Door Configuration: Double Door
  • Door Handing: Left-Hand/Inswing
  • Door Style: Traditional
  • Door Type: Exterior Prehung
  • Features: Brickmould, Lockset Bore (Double Bore), Weatherstripping
  • Finish Type: Primed
  • Frame Material: Wood
  • Hinge Finish: Satin Nickel
  • Hinge Type: Standard
  • Included: No Additional Items Included
  • Material: Steel
  • Number of Hinges: 6
  • Panel Type: 6 Panel
  • Product Weight: 99 lb
  • Returnable: 90-Day
  • Suggested Application: Back, Basement Entry, Front, Garage Entry, Side
  • Energy Star Qualified: North-Central, Northern, South-Central, Southern
  • Fire Rating: None
  • Manufacturer Warranty: 10-Year Warranty on Door Component, Limited Lifetime Warranty on Prehung MSystem

FAQ:

  • Q: What is the warranty on this door?
    A: The MMI Door Majestic Steel Front Door comes with a 10-year warranty on the door component and a limited lifetime warranty on the prehung MSystem. Note that failure to finish all six sides of the door component will void all warranties.

  • Q: Is this door energy efficient?
    A: Yes, the door features a high-density polystyrene core that provides excellent insulation, allowing it to meet or exceed current energy code standards.

  • Q: Can both doors be opened?
    A: Yes, both doors can be opened by releasing the astragal on the inactive door.

  • Q: What is included with the prehung unit?
    A: The prehung unit comes with 6 satin nickel hinges, compression weatherstrip, and a composite adjustable sill.

  • Q: Is the door ready to be painted?
    A: Yes, the door comes primed and is ready to be painted to match your home’s exterior.

  • Q: What are the suggested applications for this door?
    A: This door is suitable for various applications including back, basement entry, front, garage entry, and side entrances.

Add a touch of timeless elegance to your home with the MMI Door Classic 6-Panel Front Door, where style meets durability!

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: 71488128227

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.6 ★★★★★
Based on 24 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
O
Om S
Pawtucket, 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
Grantham, 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
Cuba, 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
Natrona Heights, 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
Houston, 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

recommand products

Long Shot (Hoops, 1)
18.99
Hush Hush
19.99
In the Shadows: A Dark Stalker Romance (The Shadows Series, 1)
19.99
In Your Dreams: A Novel (Rome, Kentucky)
19.00
Is This Real or Just Pretend?
17.99