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Lian Li O11 Dynamic EVO narrowly beats the Fractal Design North ATX Mid Tower Case in the pc cases category, especially in performance, scoring 77 vs 73. If you want the better overall pc cases, Lian Li O11 Dynamic EVO is the recommended choice.
Picking Lian Li O11 Dynamic EVO over Fractal Design North ATX Mid Tower Case means trading these off.
Scores are relative within the pc casescategory. Percentages show each dimension's weight in the overall score. A difference of less than 0.5 points is considered a tie.
✓ Pros
✗ Cons
✓ Pros
| Spec | Fractal Design North ATX Mid Tower Case | Lian Li O11 Dynamic EVOW |
|---|---|---|
| Price | 145$ | 109.99$✓ |
| Weight | 8500g✓ | 10000g |
| Dimensions | 460 x 210 x 470 mm | 510 x 230 x 466 mm |
| Colors | Charcoal Black Walnut | Black |
Buy Fractal Design North ATX Mid Tower Case if…
The Fractal Design North ATX Mid Tower Case is worth considering if you prefer its specific design, ecosystem, or brand — though it scores lower overall in our comparison.
Buy Lian Li O11 Dynamic EVO if…
Buy the Lian Li O11 Dynamic EVO if you want the best performance in this comparison. It scores higher overall and is the recommended choice for most buyers.
Lian Li O11 Dynamic EVO narrowly beats the Fractal Design North ATX Mid Tower Case in the pc cases category, especially in performance, scoring 77 vs 73. If you want the better overall pc cases, Lian Li O11 Dynamic EVO is the recommended choice.
No, Lian Li O11 Dynamic EVO scores higher (75 vs 74).
Lian Li O11 Dynamic EVO is cheaper at $109.99 vs $145 for the Fractal Design North ATX Mid Tower Case.
The Fractal Design North ATX Mid Tower Case is worth considering if you prefer its specific design, ecosystem, or brand — though it scores lower overall in our comparison.
Buy the Lian Li O11 Dynamic EVO if you want the best performance in this comparison. It scores higher overall and is the recommended choice for most buyers.
Fractal Design North ATX Mid Tower Case is lighter at 8500g vs 10000g.
Reviewed by VersusMatrix Editorial Team
Last updated: April 25, 2026
Methodology: AI-powered analysis of technical specifications from manufacturer data. Scores are calculated by comparing products across multiple dimensions and normalized relative to the full category database. Our editorial process is independent and not influenced by affiliate partnerships.
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