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Sales coaching and training · September 2026 Edition

Spekit vs Fathom

Zero of twelve models named Spekit first on the direct prompt; zero named Fathom. Spekit was named by nine of the twelve models and Fathom by eight and Spekit carries 13 labels and Fathom 12, so the shares are not directly comparable.

Spekit

accepted challenger

Named in four categories this edition.

Fathom

accepted challenger

Named in five categories this edition.

First-choice share4%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#7#8A position in a field of 17; printed, not drawn.
Labels1312A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Spekit reading right to left. Rank and label count are printed, not drawn.SalesHood was named alongside these two in eleven of the twelve direct answers. SalesHood vs Spekit · SalesHood vs Fathom · Gong vs Spekit

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the sales coaching and training page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
SpekitFirst choices, of twelve modelsFathom
Direct00
Paraphrase20
Comparative00
Budget-constrained02
Scale-constrained00
Negative001 against Spekit · 1 against Fathom
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Spekit and Fathom stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Spekit Fathom first choice named as an alternative argued againstblank: not namedEach cell is one answer, Spekit on the left and Fathom on the right.

The direct prompt

The plain question, one answer per model, grouped by where Spekit and Fathom stood in it.

Neither was the first choice, one was named

3 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Mistral SmallSalesHood alternatives: Convo, Dock, Spekit
Llama 4 MaverickRichardson Sales Performance, Sandler Training alternatives: Convo, Dock, SalesHood, Spekit
Qwen 3.7 FlashGong alternatives: Clari Copilot, HubSpot Sales Hub, SalesHood, Spekit

Neither was named

9 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Avoma alternatives: Challenger, Chorus by ZoomInfo, Gong, MindTickle
GPT-5.4 miniMindTickle alternatives: Allego, Gong, SalesHood, Second Nature
Gemini 3.5 FlashAvoma, SalesHood alternatives: Allego, Chorus by ZoomInfo, Jiminny, PitchMonster, Second Nature
Perplexity SonarMindTickle alternatives: Gong, Highspot, Jiminny, SalesHood
Grok 4.1 FastSalesHood alternatives: Allego, Gong, MindTickle
DeepSeek V4 FlashSalesHood alternatives: Avoma, Salesloft
Kimi K2SalesHood alternatives: 360Learning, Allego, Chorus by ZoomInfo, Clari Copilot
GLM 4.7 FlashXSalesHood alternatives: Allego, Learn:Up
MiniMax M2.5PitchMonster alternatives: 360Learning, Gong, SalesHood, Salesloft

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Fathom leads by thirteen points.
Fathom13%#2 of 18
Spekit0%#12 of 18
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Spekit4%#7 of 17
Fathom4%#8 of 17
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Spekit0%#– of 12
Fathom0%#– of 12
The full enterprise standing →

What the models said about Spekit

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.

“Spekit and Trainual are good for documentation/reference but don't actually provide conversation practice or skill analytics” Kimi K2 · negative prompt · soft negative
“either SalesHood ... or Spekit (if contextual learning and workflow integration are priorities)” MiniMax M2.5 · paraphrase prompt · first choice
“1. Spekit — Best for In-Workflow Training & Knowledge Delivery” Qwen 3.7 Flash · paraphrase prompt · first choice

What the models said about Fathom

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.

“AI-generated meeting summaries are sometimes criticized for missing critical context or nuance” Qwen 3.7 Flash · negative prompt · soft negative
Also compared
SalesHood vs SpekitSalesHood vs FathomGong vs SpekitGong vs FathomMindTickle vs SpekitMindTickle vs Fathom360Learning vs Spekit360Learning vs FathomChorus by ZoomInfo vs SpekitChorus by ZoomInfo vs FathomAvoma vs SpekitAvoma vs FathomAll twenty-eight head-to-head pages and the full sales coaching standing

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.