SKU: 21063478981

Manker MK35 II 6,000 Lumens 2,000 Meters Thrower King LUMINUS SBT90 GEN2 LED Flashlight with 4 x 18650 Batteries

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Description

Manker MK35 II 6,000 Lumens 2,000 Meters Thrower King LUMINUS SBT90 GEN2 LED Flashlight with 4 x 18650 BatteriesExpand your range of vision and security with the Manker M35 Long Range flashlight. The 6000 lumen output through anti reflective lenses provides a high quality, ultra bright beam with unmatched throw. Adjustable output means youll be able to use this compact flashlight in any situation. LONG RANGE BEAM: The MK35 has an incredible maximum beam distance of 2000 meters. Perfect for camping and hunting or security on large properties. ADJUSTABLE OUTPUT:

Expand your range of vision and security with the Manker M35 Long-Range flashlight. The 6000-lumen output through anti-reflective lenses provides a high-quality, ultra-bright beam with unmatched throw. Adjustable output means you’ll be able to use this compact flashlight in any situation.

LONG RANGE BEAM: The MK35 has an incredible maximum beam distance of 2000 meters. Perfect for camping and hunting or security on large properties. 

ADJUSTABLE OUTPUT: Toggle through output modes depending on the situation. It ranges a maximum output of 6000 lumens, all the way down to Moonlight mode that is perfect for small spaces or stealth.

IMPACT AND ABRASION RESISTANT: Our flashlight is made of aircraft-grade aluminum and has an impact resistance of 1 meter. The hard-anodized anti-abrasive finish prevents wear and tear.

WATERPROOF: With a waterproof standard of IPX-8, it can withstand water up to 2 meters deep and stay functional. It’s ideal for tackle boxes and emergency kits.

RECHARGEABLE: Easily monitor your battery with the capacity indicator and quickly recharge using a USB Type C/USB OTG cable. It can also function as a power bank to recharge your mobile device.

LOCKOUT MODE FOR SAFETY: Prevent unintentional activation and safety concerns with lockout mode.

Specifications:

  • Emitter: LUMINUS SBT-90 GEN2 LED
  • Maximum output: 6,000 lumens
  • Maximum beam intensity: 1,000,000cd
  • Maximum beam distance: 2,000 meters
  • Power by 4 x 18650 batteries (included)
  • Working voltage: 2.8v - 4.35v
  • Driver: Most efficient constant current circuit
  • Over-charge & over-discharge protection
  • Reverse polarity battery protection
  • Thermal protection circuit prevents overheating
  • Intelligent discharging & charging circuit integrated on battery carrier
  • USB Type-C rechargeable port for fast charging (Max. charging current / voltage: 3A, 5V)
  • Battery discharge function with included USB Type-C/USB OTG cable (Max. discharging current/voltage: 2A, 5V). Flashlight can be used as a power bank
  • Engineering Mode: Select output level for the moonlight mode
  • Lock-out mode prevents accidental activation
  • Battery capacity indicator shows battery levels at any time
  • Material: Aircraft-grade aluminum
  • Surface treatment: Premium Type-III hard-anodized anti-abrasive finish
  • Lens: Toughened ultra-clear glass lens with anti-reflective coating
  • Waterproof standard: IPX-8 (2 meters under water)
  • Impact resistance: 1 meter
  • Tail-stands
  • Size: 185mm / 7.3 inces (length) x 109mm / 4.29 inches (head diameter) x 53mm / 2.0 inches (body diameter)
  • Weight: 737 grams / 26 ounces (without batteries)

What's Included:

  • Flashlight, Batteries, Spare O-ring, Shoulder strap, USB Type-C/USB OTG cable, User Guide


Modes & Runtimes:

    • Moonlight 0.1 - 22 lumens, 120 days
    • Low 245 lumens, 20 hours
    • Medium 1: 575 lumens, 9.5 hours
    • Medium 2: 1150 lumens, 4.6 hours
    • High: 2500 lumens, 2 hours
    • Turbo 6000 lumens - 2500 lumens, 1.5 hours
    • Strobe 6000 lumens

    Operation:

    • While flashlight is off, one click to access moonlight mode (left part of the figure), single clicks cycle through each mode: Moonlight > Low > Medium > High. Long press for off.
    • While the flashlight is off, long press to access to the mode your last use as in left part of the figure (Memory function), one click to cycle. Long press for off.
    • While the flashlight is off, double click access to Turbo, one click for circle. Long press for off.
    • While the flashlight is on, double click to switch between the two groups (left and right part of the figure)

    Battery indicator on the battery carrier:

    During charging or discharging of the batteries, the battery indicator will flash indicating the current capacity based on the following flash-frequency:

    • 1 flash: Less than 25%
    • 2 flashes: 25% to 50%
    • 3 flashes: 50% to 75%
    • 4 flashes: 75% to 100%

    Solid red light means that the battery is currently recharging. Solid green light and solid white light means that the battery is fully charged. When you see a solid blue light the batteries are currently discharging (OTG).

    Operation:

    • When the flashlight is off, one click access to moonlight mode (left part of the figure), one click to cycle through modes: Moonlight > Low > Medium 1 > Medium 2 > High. Long press for off.
    • When the flashlight is off, long press to access to the mode you last used as in left part of the figure (Memory function), one click for circle. Long press for off.
    • When the flashlight is off, double click access to Turbo, one click for circle. Long press for off.
    • When the flashlight is on, double click to switch between the two groups (left and right part of the figure)

    Side switch battery indicator:

    • Blue: 50%-100%
    • Purple: 20%-50%
    • Red: less than 20%

    Lock-out:

    Long press for 4 seconds to activated lock-out. Long press again for 4 seconds to unlock.

    Engineering Mode:

    Set you ideal moonlight brightness. From any mode, 4 quick clicks to get access engineering mode. Each click to cycle through the levels. Long press on the brightness you want to set.

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        Exchange/Return Notes
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        SKU: 21063478981

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        4.8 ★★★★★
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        Walter Echo-Hawk, author of THE SEA OF GRASS.
        New York, US
        ★★★★★ 5
        Native American history at its best!
        Format: Hardcover
        Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
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        Reviewed in the United States on April 1, 2019
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        Verified Purchase
        Par
        Bozeman, US
        ★★★★★ 5
        Excellent book on ML
        Format: Paperback
        This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
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        Reviewed in the United States on December 20, 2024
        R
        Verified Purchase
        Richard Hackathorn
        Louisville, US
        ★★★★★ 5
        Excellent Textbook for Hands-On Learning of ML
        Format: Kindle
        This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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        Reviewed in the United States on February 26, 2022
        A
        Verified Purchase
        Amazon Customer
        Bozeman, US
        ★★★★★ 4
        Just learning it
        Format: Paperback
        Nice learning book just have to finish it
        WAS THIS REVIEW HELPFUL?YesReportShare
        Reviewed in the United States on December 10, 2025
        K
        Verified Purchase
        Kindle Customer
        Los Angeles, US
        ★★★★★ 5
        Very useful book
        Format: Paperback
        I use it for the machine learning class I teach.
        WAS THIS REVIEW HELPFUL?YesReportShare
        Reviewed in the United States on May 3, 2026

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