Cloud hosting · November 2026 Edition
Amazon Web Services vs Vultr
Seven of fourteen models named Amazon Web Services first on the direct prompt; zero named Vultr. Amazon Web Services was named by fourteen of the fourteen models and Vultr by thirteen and Amazon Web Services carries 61 labels and Vultr 24, so the shares are not directly comparable.
Named in six categories this edition.
Named in one category this edition.
First-choice share28%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate18%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#6A position in a field of 14; printed, not drawn.
Labels6124A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Amazon Web Services reading right to left. Rank and label count are printed, not drawn.Microsoft Azure was named alongside these two in eleven of the fourteen direct answers. Microsoft Azure vs Amazon Web Services · Microsoft Azure vs Vultr · Amazon Web Services vs DigitalOcean Droplets
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 cloud hosting page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Amazon Web ServicesFirst choices, of fourteen modelsVultr
Direct70
Paraphrase90
Comparative110
Budget-constrained013 against Amazon Web Services
Scale-constrained001 against Amazon Web Services
Negative117 against Amazon Web Services · 2 against Vultr
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Across every category in the November 2026 Edition, Amazon Web Services and Vultr were named in the same answer fifty-seven times, of the 196 answers naming Amazon Web Services and the 69 naming Vultr. In those answers Vultr took the first choice five times and Amazon Web Services thirteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Amazon Web Services and Vultr stood in it.
| 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 | | | |
Amazon Web Services Vultr first choice named as an alternative argued againstblank: not namedEach cell is one answer, Amazon Web Services on the left and Vultr on the right.The direct prompt
The plain question, one answer per model, grouped by where Amazon Web Services and Vultr stood in it.
Amazon Web Services first, Vultr not the choice
7 of 14 modelsVultr was named in the answer but not as the choice, or not at all.Gemini 3.5 FlashAmazon Web Services, Microsoft Azure alternatives: Cloudreach, Google Cloud, Mission Cloud, Rackspace Technology
Grok 4.20Amazon Web Services, Microsoft Azure alternatives: Akamai Connected Cloud, Atlantic.Net, DigitalOcean Droplets, Effectual, Expedient, Google Cloud, RapidScale
Mistral SmallAmazon Web Services alternatives: Akamai's Linode, DigitalOcean Droplets, Expedient, RapidScale
DeepSeek V4 FlashAmazon Web Services, Microsoft Azure alternatives: Akamai Connected Cloud, Atlantic.Net, DigitalOcean Droplets, Expedient, RapidScale
Llama 4 MaverickAmazon Web Services alternatives: DigitalOcean Droplets, Google Cloud, Microsoft Azure
GPT-6 LunaAmazon Web Services alternatives: Azure, Google Cloud
Muse Glimmer 30BAmazon Web Services, Microsoft Azure alternatives: Akamai's Linode, Atlantic.Net, DigitalOcean Droplets, RapidScale
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.Claude Haiku 4.5Atlantic.Net alternatives: Amazon Web Services, Cloudways, Hosting.com
GPT-5.4 miniMicrosoft Azure alternatives: Amazon Web Services, Google Cloud
Perplexity SonarMicrosoft Azure alternatives: Amazon Web Services, Google Cloud
Qwen 3.7 FlashMicrosoft Azure alternatives: Amazon Web Services, DigitalOcean Droplets, Google Cloud
Kimi K2Microsoft Azure alternatives: Amazon Web Services, DigitalOcean Droplets, Google Cloud, Vultr
GLM 4.7 FlashXAkamai Connected Cloud, Atlantic.Net, Cloudways, DigitalOcean Droplets alternatives: Amazon Web Services, Google Cloud, Microsoft Azure
MiniMax M2.5Microsoft Azure alternatives: Amazon Web Services, Google Cloud
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
Amazon Web Services leads by six points.
Amazon Web Services9%#2 of 14Vultr4%#5 of 14Mid-marketThe figures above
Amazon Web Services leads by twenty-six points.
Amazon Web Services28%#2 of 14Vultr2%#6 of 14Enterprise
Amazon Web Services leads by forty-five points.
Amazon Web Services45%#1 of 8Vultr0%#– of 8What the models said about Amazon Web Services
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid big providers like AWS, Azure, or Google Cloud unless you're using their free tiers” Grok 4.20 · budget prompt · hard negative
“Hyperscalers (AWS/Azure/GCP) can charge heavy fees to move data out of their network... High complexity; requires dedicated FinOps/DevOps; egress fees and support plans can be expensive.” Gemini 3.5 Flash · scale prompt · soft negative
“Choose AWS/Azure/GCP only if you need their broader enterprise ecosystem... enough to justify the added cost/complexity.” GPT-5.4 mini · budget prompt · soft negative
“Largest and most mature cloud platform with 200+ services... Choose AWS if you need the most services, global coverage, and proven reliability” Kimi K2 · comparative prompt · first choice
“Dominates with 200+ services, massive global infrastructure... Best for enterprises and developers needing unlimited scalability.” MiniMax M2.5 · comparative prompt · first choice
“AWS is generally the most mature and broadest cloud platform... usually the default choice if you want the widest service catalog” GPT-5.4 mini · comparative prompt · first choice
What the models said about Vultr
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“unexpected account suspensions, payment blocks, unreasonable verification demands” GLM 4.7 FlashX · negative prompt · hard negative
“Vultr scored only 1.5/5 based on customer reviews” DeepSeek V4 Flash · negative prompt · hard negative
“Linode (Akamai) or Vultr are often praised for better support than DigitalOcean” Qwen 3.7 Flash · negative prompt · first choice
“DigitalOcean or Vultr are often the best starting points” MiniMax M2.5 · budget prompt · first choice
“Vultr: Most data center locations (30+), very competitive pricing starting at $2.50/month” Kimi K2 · direct prompt · alternative
Also compared
Microsoft Azure vs Amazon Web ServicesMicrosoft Azure vs VultrAmazon Web Services vs DigitalOcean DropletsAmazon Web Services vs Akamai Connected CloudAmazon Web Services vs Atlantic.NetAmazon Web Services vs CloudwaysAmazon Web Services vs HostingerDigitalOcean Droplets vs VultrAkamai Connected Cloud vs VultrAtlantic.Net vs VultrVultr vs CloudwaysVultr vs HostingerAll twenty-eight head-to-head pages and the full cloud hosting 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.