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Description
be quiet! System Power 11 550W is ATX 3.1 compliant and PCIe 5.1 compatible, 5-year manufacturer's warrantySYSTEM POWER 11 550W Proven Reliability, Quiet Operation System Power 11 is the ATX 3. 1 PSU for value oriented PC builders that do not want to pass on reliability and quietness. Highlights ATX 3. 1 PSU with support for PCIe 5. 1 GPUs and GPUs with 6+2 pin connectors Temperature controlled 120mm quality fan reduces system noise Rock solid stability with a strong 12V rail Tight voltage regulation using DC to DC technology Up to one PCIe 5. 1 12V 2x6
SYSTEM POWER 11 550WProven Reliability, Quiet Operation System Power 11 is the ATX 3.1 PSU for value-oriented PC builders that do not want to pass on reliability and quietness.
Highlights
ATX 3.1 PSU with support for PCIe 5.1 GPUs and GPUs with 6+2 pin connectors
Temperature-controlled 120mm quality fan reduces system noise
Rock-solid stability with a strong 12V-rail
Tight voltage regulation using DC-to-DC technology
Up to one PCIe 5.1 12V-2x6 600W and up to 3 PCIe 6-2 connectors for high-end GPUs
Dependable operation to support powerful GPUs
Stand-by drain of less than 0.15 watts
80 PLUS Bronze efficiency (up to 90.0 %)
5-year manufacturer’s warranty
Product conception, design and quality control in Germany
General
Model
System Power 11 550 W
Continuous power (W)
550
Peak power (W)
No
Form factor
Version 3.1
Form factor EPS 12V
Version 2.92
Topology
Double forward + DC-DC
Digitally controlled
No
Voltage (Vac)
200 - 240
Frequency (Hz)
50
Input current (A)
4
Power factor at 100% load
>0.98
Modern standby
Yes
Power consumption in standby (W)
<0.1
Average life time (h / 25°C)
>100,000
Operating temperature up to (°C)
40
Efficiency
80 PLUS certification
Efficiency (%) at 230V, 2% load64.4 Bronze
Efficiency (%) at 230V, 10% load 84.4 Bronze
Efficiency (%) at 230V, 20% load 88.6 Bronze
Efficiency (%) at 230V, 50% load 89.7 Bronze
Efficiency (%) at 230V, 100% load 86.6 Bronze
Fan and cooling technology
Cybenetics Noise Rating
No
Fan
Silence-optimized be quiet! fan
Fan size (mm)
120
Bearing technology
Rifle
Motor technology
4-pole fan motor
Max. fan speed (rpm)
1800
dB(A) at 10% load
10.4
dB(A) at 20% load
10.8
dB(A) at 50% load
11.0
dB(A) at 100% load
24.2
Output
Multi-rail operation (12V rails)
No
12V single rail operation
Yes
Overclocking key
No
+3.3V (A)
20
+5V (A)
20
+12V1 (A)
45.83
+12V2 (A)
no
+12V3 (A)
No
+12V4 (A)
No
+12V5 (A)
No
+12V6 (A)
No
-12V (A)
0.3
+5Vsb (A)
3
Max. combined power 12V (W)
550
Max. combined power 12V-2x6 (W)
300
Max. combined power 3.3V + 5V (W)
120
Hold-up time at 100% load (ms)
16.86
Hold-up time at 80% load (ms)
20.92
Power good signal (ms)
100 - 150
Cables and connectors
Modular cables
No
Sleeved cables
P24
Flat cables
P4+4, P4, PCIe, drives
Maximum cable length (cm)
55
Cable length to motherboard (cm)
79
No. of cables
7
ATX-Motherboard (20+4-pin)
1
P4+4 (CPU)
1
P8 (CPU)
No
P4 (CPU)
1
12V-2x6 cables
1
PCI-e 6+2-pin (GPU)
2
PCI-e 6-pin (GPU)
No
SATA
5
PATA
1
FDD (Floppy)
No
Protection
OTP (over temperature protection)
Yes
OCP (over current protection)
Yes
OPP (over power protection)
Yes
SCP (short circuit protection)
yes
OVP (over Voltage protection)
Yes
UVP (under Voltage protection)
Yes
SIP (Surge & Inrush protection)
Yes
Safety certification
BSMI
No
CB
No
CCC
No
CE
Yes
cRUus
No
cTUVus
No
CU
Yes
FCC
No
RCM
No
TUV
Yes
UKCA
Yes
IRAM
No
Environmental directives
ErP
Yes
WEEE
Yes
RoHS
Yes
Triman
No
Scope of delivery
Thumb screws
No
Screws
Yes
Cable ties
Yes
Velcro cable ties
No
User manual languages
No
OCK slot bracket with switch / OCK jumper
No
SFX-to-ATX adapter bracket
No
Casing
Dimensions without cable (L x W x H), (mm)
86 x 150 x 140
Weight (kg)
1.92
Color
Black
Logistics data and RRP
Dimensions, package (L x W x H), (mm)
268 x 195 x 97
Gross weight, package (kg)
2.3
Pieces per packaging unit
6
Dimensions, shipping box (L x W x H), (mm)
556 x 311 x 218
Gross weight, shipping box (kg)
14.9
Service
Warranty (Years)
5
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- 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
4.0 ★★★★★
Based on 13 reviews
Sort
Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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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