Overview Leaderboard Methodology
Industry Report

Cutlery Brands

Companies producing kitchen knives, knife blocks, and related sharpening tools for home cooks and professional chefs.

Brands tracked: 38
Brands analyzed: 38
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 288
Total responses: 1,495
Top Brand Overall?
Wüsthof
88/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Wüsthof
91

Highest score on the LBA metric.

Authority Leader?
Wüsthof
76

Highest score on the Authority metric.

TOM Leader?
Wüsthof
97

Highest score on the TOM metric.

Wüsthof is the default answer in AI responses for Cutlery Brands

When users ask ChatGPT, Claude, or Gemini about Cutlery Brands, Wüsthof is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Victorinox is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 38 Cutlery Brands brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Wüsthof
wusthof.com
 91
76
97
88
2
Victorinox
victorinox.com
 82
57
77
71
3
Zwilling
zwilling.com
 85
36
88
65
4
Shun
kaiusa.com
 87
42
68
63
5
Henckels
henckels.com
 79
26
82
55
6
M
Miyabi
miyabi-knives.com
 86
24
56
49
7
Global
globalcutleryusa.com
 82
19
66
47
8
Tojiro
tojiro-japan.com
 76
33
32
43
9
Oneida
oneida.com
 68
3
38
19
10
Mercer Culinary
mercerculinary.com
 68
5
11
15
11
Messermeister
messermeister.com
 74
2
20
14
12
S
Sakai Takayuki
sakai-takayuki.com
 76
1
6
8
13
Cuisinart
cuisinart.com
 70
1
3
6
14
Misen
misen.com
 69
2
1
5
15
Fortessa
fortessa.com
 56
0
29
3
16
Lenox
lenox.com
 63
0
26
3
17
Y
Yoshihiro
yoshihiro-cutlery.com
 63
1
0
3
18
C
Cambridge Silversmiths
cambridgesilversmiths.com
 37
0
17
2
19
Mikasa
mikasa.com
 59
0
21
2
20
M
Misono
misono-hamono.com
 71
0
8
2
21
Cangshan
cangshancutlery.com
 57
0
3
1
22
Cutco
cutco.com
 77
0
1
1
23
Dalstrong
dalstrong.com
 73
0
4
1
24
F. Dick
fdick.com
 77
0
2
1
25
Kramer
kramerknives.com
 65
0
0
1
26
M
MAC Knife
macknife.com
 79
0
4
1
27
Opinel
opinel.com
 79
0
0
1
28
Robert Welch
robertwelch.com
 68
0
0
1
29
T
Takamura
takamura-hamono.com
 65
0
2
1
30
Arcos
arcos.com
 75
0
0
0
31
Dexter-Russell
dexterrussellcutlery.com
 70
0
0
0
32
Güde
guede-solingen.de
 62
0
0
0
33
K
K Sabatier
ksabatier.com
 55
0
0
0
34
Lamson
lamsonproducts.com
 52
0
0
0
35
Lion Sabatier
lionsabatier.com
 56
0
0
0
36
M
Masamoto Sohonten
masamoto-sohonten.co.jp
 70
0
0
0
37
Rada Cutlery
radacutlery.com
 68
0
0
0
38
Suncraft
suncraft.co.jp
 55
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 288 shared Cutlery Brands prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 288 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →