| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Coaching platforms | Learning and development | 11% | 3 of 128 | 15% | 20 | accepted challenger | ▼−1Since September 2026: 7% → 6%, −1 point. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Mentoring software | Learning and development | 0% | 38 of 77 | 0% | 1 | under 10 labels · led by Together at 28% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Coaching platforms | 7% | 6% | ▼−1Since September 2026: 7% → 6%, −1 point. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 4 → 3 of 128 |
| Mentoring software | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 18 → 38 of 77 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 0 | 0 | 0 | 1 |
| GPT-5.4 mini | 0 | 1 | 0 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 1 | 2 |
| Perplexity Sonar | 1 | 0 | 0 | 0 | 1 |
| Grok 4.1 Fast | 0 | 1 | 1 | 0 | 2 |
| Mistral Small | 0 | 0 | 1 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 2 | 1 | 0 | 3 |
| Llama 4 Maverick | 1 | 0 | 0 | 0 | 1 |
| Qwen 3.7 Flash | 0 | 1 | 0 | 0 | 1 |
| Kimi K2 | 0 | 1 | 1 | 0 | 2 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 1 | 1 |
| GPT-6 Luna | 1 | 1 | 0 | 0 | 2 |
| Muse Glimmer 30B | 2 | 0 | 0 | 1 | 3 |
Verbatim evidence the judge attached to positive labels.
“"Torch — Best for Leadership Development in Mid-Market Companies"... Choose Torch if you want a leadership / manager-to-executive pipeline with curated coaches” Muse Glimmer 30B · Coaching platforms · direct prompt · first choice
“The best employee coaching platforms for a mid-market B2B company include Torch, Growthspace, Lattice, and Motivosity.” Llama 4 Maverick · Coaching platforms · direct prompt · first choice
“Torch is a leadership coaching and alignment platform built for mid-market and enterprise talent teams” Claude Haiku 4.5 · Coaching platforms · direct prompt · first choice
“Torch is the named best fit for 500–5,000 employee companies” Muse Glimmer 30B · Coaching platforms · paraphrase prompt · first choice
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Enterprise platforms to avoid (for tight budgets): BetterUp, CoachHub, Torch, and EZRA” MiniMax M2.5 · Coaching platforms · budget prompt · hard negative
“Many of these platforms have incredibly strict non-compete clauses.” Gemini 3.5 Flash · Coaching platforms · negative prompt · soft negative
“are quote-based and priced for mid-market / enterprise populations” Muse Glimmer 30B · Coaching platforms · budget prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 66 of the 68 answers that named Torch and are not a share of its labels.
237 of the 265 domain citations in answers naming Torch came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 250 | 3 | 2026-08-27 | Succession planning, Performance management | |
| Webinar or virtual event | 46 | 0 | 2025-11-07 | ||
| Report or ebook | 38 | 0 | 2025-01-17 | Succession planning | |
| News or press | 21 | 0 | 2025-12-11 | ||
| Conference or event | 17 | 0 | 2025-10-16 | ||
| Glossary or explainer | 15 | 1 | 2026-08-27 | ||
| Comparison | 8 | 1 | 2026-07-08 | ||
| Case study | 1 | 0 | 2025-01-09 |
Every page torch.io exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
What Torch's own pages state, read September 28, 2026: torch.io, trust.torch.io, torch.io/product, torch.io/customer-stories. A claimed page can correct any of them.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Torch's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Torch, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Torch by email, built from the raw record of the edition. It shows:
Torch is among the products AI models recommend first in Coaching platforms this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.