n8n vs Make
One of fourteen models named n8n first on the direct prompt; two named Make. n8n was named by thirteen of the fourteen models and Make by twelve and n8n carries 32 labels and Make 29, so the shares are not directly comparable.
Named in three categories this edition.
Named in three categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 workflow orchestration page.
By framing
n8nFirst choices, of fourteen modelsMake
Across every category in the November 2026 Edition, n8n and Make were named in the same answer ninety times, of the 123 answers naming n8n and the 155 naming Make. In those answers Make took the first choice twenty-eight times and n8n fourteen.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | |||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | | | ||||
| Perplexity Sonar | | | | | ||
| Grok 4.20 | | | | |||
| Mistral Small | | | ||||
| DeepSeek V4 Flash | | | ||||
| Llama 4 Maverick | | | ||||
| Qwen 3.7 Flash | | | ||||
| Kimi K2 | | | ||||
| GLM 4.7 FlashX | | | | |||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | | | ||||
| Muse Glimmer 30B | | |
n8n Make first choice named as an alternative argued againstblank: not namedEach cell is one answer, n8n on the left and Make on the right.The direct prompt
n8n first, Make an alternative
1 of 14 modelsMake was named in the answer but not as the choice, or not at all.Make first, n8n an alternative
2 of 14 modelsn8n was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 of 14 modelsThe answer made no first choice from these two in this category.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
What the models said about n8n
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Self-hosting avoids some vendor costs but transfers responsibility for security patches, backups, upgrades, availability, and monitoring to your team” Perplexity Sonar · negative prompt · soft negative
“For most budget-conscious companies with some technical capability, n8n offers the best balance of features, flexibility, and cost.” GLM 4.7 FlashX · budget prompt · first choice
“For most small teams, n8n (open-source, self-hosted) or Zapier (no-code, free tier) are the best starting points” Mistral Small · budget prompt · first choice
“For a company with a limited budget, n8n (self-hosted) is almost always the best choice.” DeepSeek V4 Flash · budget prompt · first choice
What the models said about Make
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“It's best avoided for complex or high-volume workflows.” Mistral Small · negative prompt · hard negative
“Zapier, Make, or similar automation tools for high-volume, mission-critical processes” Perplexity Sonar · negative prompt · soft negative
“be cautious for complex, high-scale, or mission-critical orchestration” Grok 4.20 · negative prompt · soft negative
“The Best Overall (Visual & Complex Logic): Make (formerly Integromat) ... Make is currently the strongest contender.” Qwen 3.7 Flash · direct prompt · first choice
“the top recommendation for most mid‑market B2B organizations is: Make (formerly Integromat)” GLM 4.7 FlashX · direct prompt · first choice
“Make is generally considered the best balance between power and cost for most businesses.” Qwen 3.7 Flash · budget prompt · first choice
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.