best spd pedals DEL Gravel Race Clipless Pedal – Wolf Tooth Components
SKU: 90665998502
best spd pedals

best spd pedals DEL Gravel Race Clipless Pedal – Wolf Tooth Components

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Description

best spd pedals DEL Gravel Race Clipless Pedal – Wolf Tooth ComponentsWolf Tooth DEL Gravel Race Clipless Pedals feature a one sided design for peak speed and consistent performance in gravel races. These SPD compatible bike pedals are exceptionally lightweight at only 216 g, while still featuring a large platform for maximum power transfer and a connected feel that approaches that of a road pedal. The one sided design features an open center between the binding cages for mud shedding. It has all the advantages of a

Wolf Tooth DEL Gravel Race Clipless Pedals feature a one-sided design for peak speed and consistent performance in gravel races. These SPD-compatible bike pedals are exceptionally lightweight at only 216 g, while still featuring a large platform for maximum power transfer and a connected feel that approaches that of a road pedal. The one-sided design features an open center between the binding cages for mud shedding. It has all the advantages of a road pedal, but with a shoe and cleat system that works in all conditions. 

The DEL Gravel Race Clipless Pedals have an adjustable Q factor of 4 mm increments. Inside the pedal is a stainless steel axle, three bearings, and two spacer. The spacers and bearings can be rearranged for Q factors of 51, 55, or 59 mm. This is simple enough for anyone to do at home. A spacer kit including four 2 mm spacers is available for purchase to further fine tune Q Factor adjustment. Like most Wolf Tooth components and accessories, replacement parts and service guides are available via Wolf Tooth Right to Repair. 

  • Thinner than the competition at 14.7 mm (compared to Xpedo MF8 at 17 mm, Shimano XTR 9200 at 16.5 mm, and Eggbeater 3 at 17 mm)
  • Lighter weight than the competition at 216 g (compared to Xpedo MF8 at 220 g, Shimano XTR 9200 at 316 g, and Eggbeater 3 at 265 g)
  • Larger platform area for power transfer than the competition at 559 mm² (compared to Xpedo MF8 at 46 mm², Shimano XTR 9200 at 144 mm² and Eggbeater 3 at 102 mm²)
  • Adjustable Q factor options of 51, 55, and 59 mm (53 and 57 mm also available via spacer kit sold separately). Pedals ship in 55 mm position.
  • 5 degrees float | 12 degrees release
  • SPD compatible
  • Proven axle and bearing design from Waveform Aluminum Pedals
  • Designed, tested, and machined at Wolf Tooth in Minnesota, USA

Recommended

Compatibility

  • Compatible with SPD cleats; Wolf Tooth cleats included
  • Fits all standard cranks with 9/16-20 tpi right- and left-hand threads – some kid’s bikes and vintage bikes may have smaller incompatible threads.

Tech Specs

Weight:  216g

Material:
Body: 6061-T6 aluminum CNC machined
Axle: heat-treated 17-4 PH stainless steel
Binding Cage: stainless steel; Hardware: stainless steel

Included:  pedals, cleats with shims and bolts

Patent Pending

Machined in the USA

Patent and trademark information

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SKU: 90665998502

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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
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Pawtucket, 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
Lake Worth, 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.
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Reviewed in the United States on August 10, 2025
V
Vineeth Sai
Waukegan, 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
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Verified Purchase
CL
Lake Worth, 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

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