GTM AI Index
Index Marketing Webinars › Goldcast vs BigMarker
Webinar and virtual event platforms · September 2026 Edition

Goldcast vs BigMarker

Four of twelve models named Goldcast first on the direct prompt; one named BigMarker. Goldcast was named by eleven of the twelve models and BigMarker by eleven and Goldcast carries 20 labels and BigMarker 21, so the shares are not directly comparable.

Goldcast

accepted challenger

Named in three categories this edition.

BigMarker

accepted challenger

Named in one category this edition.

First-choice share14%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%5%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 19; printed, not drawn.
Labels2021A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Goldcast reading right to left. Rank and label count are printed, not drawn.Livestorm was named alongside these two in nine of the twelve direct answers. Livestorm vs Goldcast · Livestorm vs BigMarker · Demio vs Goldcast

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 webinar and virtual event platforms page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
GoldcastFirst choices, of twelve modelsBigMarker
Direct41
Paraphrase201 against Goldcast
Comparative00
Budget-constrained00
Scale-constrained00
Negative001 against BigMarker
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 Goldcast and BigMarker 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
Goldcast BigMarker first choice named as an alternative argued againstblank: not namedEach cell is one answer, Goldcast on the left and BigMarker on the right.

The direct prompt

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

Goldcast first, BigMarker not the choice

4 of 12 modelsBigMarker was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashGoldcast alternatives: Airmeet, Demio, Livestorm
Perplexity SonarGoldcast alternatives: Bizzabo, GoTo Webinar, Livestorm
Mistral SmallGoldcast alternatives: Demio, Livestorm, Zoom Webinars
Qwen 3.7 FlashGoldcast alternatives: Livestorm, ON24, Zoom Webinars

BigMarker first, Goldcast an alternative

1 of 12 modelsGoldcast was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5BigMarker alternatives: Demio, GoTo Webinar, Goldcast, Livestorm

Neither was the first choice, one was named

4 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Grok 4.1 FastDemio alternatives: GoTo Webinar, Goldcast, Livestorm, ON24, Zoom Webinars
DeepSeek V4 FlashLivestorm alternatives: Demio, Goldcast
Kimi K2Demio, Livestorm alternatives: BigMarker, Goldcast
MiniMax M2.5Demio alternatives: Bizzabo, Goldcast, Livestorm

Neither was named

3 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniDemio alternatives: ON24
Llama 4 Maverickno first choice
GLM 4.7 FlashXGoTo Webinar alternatives: Airmeet, ClickMeeting, Cvent, Demio, EventMobi, PheedLoop, WebinarJam, Whova, Zoom Webinars, Zuddl

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
Level: the same share of first choices.
Goldcast0%#– of 16
BigMarker0%#15 of 16
The full small business standing →
Mid-marketThe figures above
Goldcast leads by eleven points.
Goldcast14%#3 of 19
BigMarker2%#7 of 19
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Goldcast4%#8 of 16
BigMarker4%#7 of 16
The full enterprise standing →

What the models said about Goldcast

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

“ON24 and Goldcast ... typically overkill and not transparent in cost for a mid-sized company” DeepSeek V4 Flash · paraphrase prompt · hard negative
“Goldcast is widely considered the top tier choice for B2B marketing teams” Qwen 3.7 Flash · direct prompt · first choice
“🥇 Gold Standard: Goldcast ... Built specifically for B2B marketers” Mistral Small · direct prompt · first choice
“Goldcast: Best Overall for B2B Demand Gen & Marketing ROI” Gemini 3.5 Flash · paraphrase prompt · first choice

What the models said about BigMarker

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

“BigMarker (poor offer pop-ups, glitchy screen sharing, pricey)” Grok 4.1 Fast · negative prompt · soft negative
“Supports live, simulive, automated, and on-demand webinars natively from one platform, and fits mid-market to enterprise teams” Claude Haiku 4.5 · direct prompt · first choice
“Choose BigMarker or ON24 if you're running large-scale, highly controlled, analytics-heavy enterprise events” Perplexity Sonar · paraphrase prompt · alternative
“Branded automation & series ... Evergreen sessions, custom landing pages | Pricing not transparent” Grok 4.1 Fast · comparative prompt · alternative
Also compared

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.