Cloud GPU platform engine breadth

As of

All 16 companies by engine breadth

Runpod leads at 3 engines; the middle of the board sits at 2.

Ahead of second place: 0
Held by the top three: 36%
Middle of the board: 2
Below half the leader: 7 of 16

Rank, name and engine breadthMiddle 2

1Runpod3 engines
2Lambda Cloud3 engines
3Vast.ai3 engines
4Google Cloud2 engines
5CoreWeave2 engines
6Microsoft Azure2 engines
7Paperspace2 engines
8Hyperstack2 engines
9IBM Cloud2 engines
10Crusoe Cloud1 engines
11Nebius AI Cloud1 engines
12Amazon EC21 engines
13Oracle Cloud Infrastructure1 engines
14Akash Network0 engines
15Fluidstack0 engines
16Voltage Park0 engines

The prompt boards are re-run in rotation, about one category a day, so each board refreshes every few weeks and shows the date of its snapshot.

3 checks behind each row · 100% confidence across rows.

Cloud GPU platforms engine breadth current rankings
Rank	Name	Engine breadth	Mention coverage	Share of names	Cited as source	Change	Why
01	Runpod	3 engines	44.44% · 16 / 36	18.82% · 16 / 85	42.42% · 14 / 33		This rank My rank
02	Lambda Cloud	3 engines	38.89% · 14 / 36	16.47% · 14 / 85	27.27% · 9 / 33	2	This rank My rank
03	Vast.ai	3 engines	22.22% · 8 / 36	9.41% · 8 / 85	0% · 0 / 33	5	This rank My rank
04	Google Cloud	2 engines	36.11% · 13 / 36	15.29% · 13 / 85	12.12% · 4 / 33	2	Showing My rank
05	CoreWeave	2 engines	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33		This rank My rank
06	Microsoft Azure	2 engines	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33	3	This rank My rank
07	Paperspace	2 engines	11.11% · 4 / 36	4.71% · 4 / 85	6.06% · 2 / 33	8	This rank My rank
08	Hyperstack	2 engines	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	1	This rank My rank
09	IBM Cloud	2 engines	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	2	This rank My rank
10	Crusoe Cloud	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33	4	This rank My rank
11	Nebius AI Cloud	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33	1	This rank My rank
12	Amazon EC2	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
13	Oracle Cloud Infrastructure	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
14	Akash Network	0 engines	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
15	Fluidstack	0 engines	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
16	Voltage Park	0 engines	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33		This rank My rank

3 checks behind each row · 100% confidence across rows.

Cloud GPU platforms engine breadth current rankings
Rank	Name	Engine breadth	Mention coverage	Share of names	Cited as source	Change	Why
01	Runpod	3 engines	44.44% · 16 / 36	18.82% · 16 / 85	42.42% · 14 / 33		This rank My rank
02	Lambda Cloud	3 engines	38.89% · 14 / 36	16.47% · 14 / 85	27.27% · 9 / 33	2	This rank My rank
03	Vast.ai	3 engines	22.22% · 8 / 36	9.41% · 8 / 85	0% · 0 / 33	5	This rank My rank
04	Google Cloud	2 engines	36.11% · 13 / 36	15.29% · 13 / 85	12.12% · 4 / 33	2	Showing My rank
05	CoreWeave	2 engines	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33		This rank My rank
06	Microsoft Azure	2 engines	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33	3	This rank My rank
07	Paperspace	2 engines	11.11% · 4 / 36	4.71% · 4 / 85	6.06% · 2 / 33	8	This rank My rank
08	Hyperstack	2 engines	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	1	This rank My rank
09	IBM Cloud	2 engines	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	2	This rank My rank
10	Crusoe Cloud	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33	4	This rank My rank
11	Nebius AI Cloud	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33	1	This rank My rank
12	Amazon EC2	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
13	Oracle Cloud Infrastructure	1 engines	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
14	Akash Network	0 engines	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
15	Fluidstack	0 engines	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
16	Voltage Park	0 engines	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33		This rank My rank

Primary brandQuestion typeModel APIQuestion contains

Run a question live

30.6%

of these answers name or cite CoreWeave

11 of 36 answers

40.7%

Its share of the compared brands' appearances

0

Answers citing its own site

0 links to its domains

2 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
Lambda Cloudlambda.ai	38.9%14 of 36	+8.3 pts	51.9%	29	5	9	3 of 3
CoreWeavecoreweave.com	30.6%11 of 36	Primary	40.7%	19	0	0	2 of 3
Crusoe Cloudcrusoe.ai	2.8%1 of 36	-27.8 pts	3.7%	1	1	1	1 of 3
Nebius AI Cloudnebius.com	2.8%1 of 36	-27.8 pts	3.7%	2	1	1	1 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01Which cloud GPU platforms are best for reliable multi-node training of large foundation models?Recommendation	CoreWeaveLambda Cloud 5 sources`e26df8b1`	None named 0 sources`dd4afeab`	CoreWeaveLambda Cloud 7 sources`42e44b3b`
02Recommend cloud GPU providers with transparent on-demand access to H100 or H200 instances and no long-term commitment.Recommendation	CoreWeaveLambda Cloud, cited 1 6 sources`b4cdad7f`	Lambda Cloud, cited 2 6 sources`389992af`	CoreWeaveLambda Cloud, cited 1 8 sources`44e25546`
03Which GPU clouds are strongest for reserving hundreds of tightly networked accelerators for a multi-month training program?Recommendation	CoreWeaveLambda Cloud 6 sources`cf645d59`	None named 0 sources`1618941d`	CoreWeaveLambda Cloud 7 sources`63153df5`
04Recommend a GPU cloud for autoscaling production inference with custom containers, scale-to-zero, and predictable cold starts.Recommendation	None named 6 sources`2e810747`	None named 0 sources`31289165`	None named 7 sources`b70c0396`
05What GPU cloud should a startup use for fast self-service access, clear hourly pricing, persistent storage, and simple deployment?Recommendation	Lambda Cloud 7 sources`38feeacf`	Lambda Cloud, cited 4 8 sources`66c62ad8`	None named 9 sources`ab64d39b`
06Which GPU cloud platforms are best for an enterprise requiring private networking, compliance controls, auditability, and support?Recommendation	CoreWeaveLambda Cloud 5 sources`4712904b`	None named 0 sources`ded18530`	None named 8 sources`15999442`
07Recommend GPU infrastructure providers with broad regional capacity, current accelerator availability, and data-residency options.Recommendation	CoreWeaveLambda Cloud 7 sources`c7c938a5`	None named 0 sources`3ac9297a`	CoreWeaveLambda Cloud 8 sources`dcd37607`
08Which GPU clouds offer strong managed Kubernetes or Slurm support for distributed AI training and inference?Recommendation	CoreWeaveNebius AI Cloud, cited 1 7 sources`dacd6580`	None named 0 sources`5e058ae3`	Crusoe Cloud, cited 1 9 sources`e2bfa496`
09Compare cloud GPU platforms on availability, accelerator breadth, interconnect, storage, reliability, support, and developer experience.Commercial comparison	CoreWeaveLambda Cloud 7 sources`a86dbb68`	None named 0 sources`7ee88389`	None named 6 sources`96362ac0`
10How should a buyer compare GPU cloud pricing across on-demand, spot, reserved, bare-metal, and committed-capacity contracts?Commercial comparison	None named 6 sources`b4bc35ba`	None named 0 sources`301e1970`	None named 5 sources`48e89e4c`
11Create a proof-of-concept scorecard for evaluating GPU clouds on real workload throughput, failure recovery, networking, and total cost.Commercial comparison	None named 0 sources`fc834653`	None named 0 sources`78741630`	Lambda Cloud, cited 1 4 sources`47480766`
12Which criteria expose capacity, interruption, egress, quota, and vendor lock-in risk when selecting a cloud GPU provider?Commercial comparison	None named 9 sources`dfe95a7e`	None named 0 sources`51ee7ab8`	None named 5 sources`dba5c807`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
runpod.io	14	2	2	1
gmicloud.ai	11	9	2	2
reddit.com	9	8	3	1
northflank.com	8	5	2	1
spheron.network	7	7	3	2
modal.com	6	8	2	1
youtube.com	5	6	3	2
lambda.ai	5	3	3	1
rank.ai	5	3	2	1
medium.com	4	4	3	2
onesourcecloud.net	4	4	2	2
fluence.ai	4	2	2	1
cloud.google.com	3	2	1	1
deploybase.ai	3	2	2	4
getdeploying.com	3	1	2	1
forums.developer.nvidia.com	2	2	2	2
akamai.com	2	2	1	3
cudocompute.com	2	2	2	3
vcluster.com	2	2	1	3
linkedin.com	2	2	1	4

What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.cloud-gpu-platforms-2026-07-27 / 4-cloud-gpu-platforms-2026-07-27-models-64232fd32583

Primary brandQuestion typeModel APIQuestion contains

Run a question live

30.6%

of these answers name or cite CoreWeave

11 of 36 answers

40.7%

Its share of the compared brands' appearances

0

Answers citing its own site

0 links to its domains

2 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
Lambda Cloudlambda.ai	38.9%14 of 36	+8.3 pts	51.9%	29	5	9	3 of 3
CoreWeavecoreweave.com	30.6%11 of 36	Primary	40.7%	19	0	0	2 of 3
Crusoe Cloudcrusoe.ai	2.8%1 of 36	-27.8 pts	3.7%	1	1	1	1 of 3
Nebius AI Cloudnebius.com	2.8%1 of 36	-27.8 pts	3.7%	2	1	1	1 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01Which cloud GPU platforms are best for reliable multi-node training of large foundation models?Recommendation	CoreWeaveLambda Cloud 5 sources`e26df8b1`	None named 0 sources`dd4afeab`	CoreWeaveLambda Cloud 7 sources`42e44b3b`
02Recommend cloud GPU providers with transparent on-demand access to H100 or H200 instances and no long-term commitment.Recommendation	CoreWeaveLambda Cloud, cited 1 6 sources`b4cdad7f`	Lambda Cloud, cited 2 6 sources`389992af`	CoreWeaveLambda Cloud, cited 1 8 sources`44e25546`
03Which GPU clouds are strongest for reserving hundreds of tightly networked accelerators for a multi-month training program?Recommendation	CoreWeaveLambda Cloud 6 sources`cf645d59`	None named 0 sources`1618941d`	CoreWeaveLambda Cloud 7 sources`63153df5`
04Recommend a GPU cloud for autoscaling production inference with custom containers, scale-to-zero, and predictable cold starts.Recommendation	None named 6 sources`2e810747`	None named 0 sources`31289165`	None named 7 sources`b70c0396`
05What GPU cloud should a startup use for fast self-service access, clear hourly pricing, persistent storage, and simple deployment?Recommendation	Lambda Cloud 7 sources`38feeacf`	Lambda Cloud, cited 4 8 sources`66c62ad8`	None named 9 sources`ab64d39b`
06Which GPU cloud platforms are best for an enterprise requiring private networking, compliance controls, auditability, and support?Recommendation	CoreWeaveLambda Cloud 5 sources`4712904b`	None named 0 sources`ded18530`	None named 8 sources`15999442`
07Recommend GPU infrastructure providers with broad regional capacity, current accelerator availability, and data-residency options.Recommendation	CoreWeaveLambda Cloud 7 sources`c7c938a5`	None named 0 sources`3ac9297a`	CoreWeaveLambda Cloud 8 sources`dcd37607`
08Which GPU clouds offer strong managed Kubernetes or Slurm support for distributed AI training and inference?Recommendation	CoreWeaveNebius AI Cloud, cited 1 7 sources`dacd6580`	None named 0 sources`5e058ae3`	Crusoe Cloud, cited 1 9 sources`e2bfa496`
09Compare cloud GPU platforms on availability, accelerator breadth, interconnect, storage, reliability, support, and developer experience.Commercial comparison	CoreWeaveLambda Cloud 7 sources`a86dbb68`	None named 0 sources`7ee88389`	None named 6 sources`96362ac0`
10How should a buyer compare GPU cloud pricing across on-demand, spot, reserved, bare-metal, and committed-capacity contracts?Commercial comparison	None named 6 sources`b4bc35ba`	None named 0 sources`301e1970`	None named 5 sources`48e89e4c`
11Create a proof-of-concept scorecard for evaluating GPU clouds on real workload throughput, failure recovery, networking, and total cost.Commercial comparison	None named 0 sources`fc834653`	None named 0 sources`78741630`	Lambda Cloud, cited 1 4 sources`47480766`
12Which criteria expose capacity, interruption, egress, quota, and vendor lock-in risk when selecting a cloud GPU provider?Commercial comparison	None named 9 sources`dfe95a7e`	None named 0 sources`51ee7ab8`	None named 5 sources`dba5c807`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
runpod.io	14	2	2	1
gmicloud.ai	11	9	2	2
reddit.com	9	8	3	1
northflank.com	8	5	2	1
spheron.network	7	7	3	2
modal.com	6	8	2	1
youtube.com	5	6	3	2
lambda.ai	5	3	3	1
rank.ai	5	3	2	1
medium.com	4	4	3	2
onesourcecloud.net	4	4	2	2
fluence.ai	4	2	2	1
cloud.google.com	3	2	1	1
deploybase.ai	3	2	2	4
getdeploying.com	3	1	2	1
forums.developer.nvidia.com	2	2	2	2
akamai.com	2	2	1	3
cudocompute.com	2	2	2	3
vcluster.com	2	2	1	3
linkedin.com	2	2	1	4

What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.cloud-gpu-platforms-2026-07-27 / 4-cloud-gpu-platforms-2026-07-27-models-64232fd32583

Ranks a reviewed Cloud GPU Platforms brand universe using a fixed, public set of neutral commercial prompts across 3 AI providers.

4

Rank on this board

2 engines

Score

3

Answers behind the score

100% confidence · 1 of 1 components evidenced

What the score is built from

1 of 1 evidenced

Every component evidenced · 1 evidence record each

Components of Google Cloud's score
Component	Value	Contribution
Engine breadth	2	2

Moved down since the previous snapshot

-2 places

Gemini brand recommendation presence50 to 75
+25
OpenAI brand recommendation presence75 to 50
-25
Gemini brand mention coverage50 to 66.667
+16.667
OpenAI brand mention coverage58.333 to 41.667
-16.667
Gemini brand citation share13.333 to 26.667
+13.333
OpenAI brand citation share9.091 to 0
-9.091
Mention share20.313 to 15.294
-5.018
Citation share11.538 to 12.121
+0.583
Anthropic brand mention coverage0 to 0
0
Anthropic brand recommendation presence0 to 0
0
Engine breadth2 to 2
0
Mention coverage36.111 to 36.111
0
Recommendation presence41.667 to 41.667
0

Where each number comes from

14 public records

Anthropic citation shareAnthropic brand citation share · observed Sep 17, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Anthropic mention coverageAnthropic brand mention coverage · observed Sep 17, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"cloud-gpu-platforms-2026-07-27","runArtifactIds":["040752d4-8eb8-4acd-b686-8d970c3981d3","d73f0f1c-aa9e-4d44-b837-9eef2f4144b8","cf0e71f7-5df4-4826-977f-82ac3bda8f59","a7ebdd3a-b8c1-457a-a226-0eb276e25477","a9d4f2fe-2534-41e6-a6c7-5d66bc9247f6","9cbc4ef3-ee08-4bc0-aefb-d72330dfbf40","11a21777-2424-43c2-a1bf-711b9f7f0c7c","6daa38c8-aaf6-4660-9578-99beb9bec360","604c8aa4-4c25-4c36-acbf-031c38489fc9","e8556831-d924-4a97-bbca-c0d9b377a087","eb876571-0eef-4351-8b48-dd3f62664866","a5411302-a7e4-43af-a185-4a7d9f8d65e1","d24f2813-c426-4532-a194-bd957de6a9b4","a518ca7e-7ad2-4379-8e6d-3c931ca294b5","79ab50b5-45b1-4119-adbd-02f37cf2d06f","24c39e21-23c6-42c7-9236-df677eb00404","a1f329a8-acd2-44fb-8f52-cea6cd81c08f","b25ffa06-1225-44cc-b259-9a178aa39fd5","7fd5fdab-821c-4c95-8d6a-934abe04fa6a","07de9229-90c1-4f33-8946-6119b25b8d82","ee148445-8df9-44e7-a821-5bd8ce23ff2b","9c75e385-a818-46fd-a539-6171c4cb8ce0","5aea5e42-c668-40b4-bbb9-8b981616ba25","a305b1cd-5522-412c-bbdc-2ee9e43b9acc","6ff794a4-a3fe-4e4f-84d4-c6895a39d065","538519fc-9b22-46fd-a3a9-4f6b34545d3f","43a87aa6-3069-4ed4-82fd-a367236145c8","285699cb-e4ec-4ad7-8b87-86276027fbb4","1e797edf-d178-426a-9199-538b67b761b1","08871839-2509-4447-bd71-40dcbd35c2d4","87acbce0-3e5c-4376-9479-19a78ac5ffa6","1292ed23-b3ee-446a-a00c-a9da79723573","f2554213-5548-4fc2-ba43-5f5a2614254a","fff6aa60-2b84-4c50-8183-f300d57e9097","1f8815d0-a3ef-4820-b756-d42535c584b3","b574df36-f648-4bfa-a517-b521532ad8ae"],"benchmarkVersion":"4-cloud-gpu-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Anthropic recommendation-prompt presenceAnthropic brand recommendation presence · observed Sep 17, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Citation shareCitation share · observed Sep 17, 2026, 12:00 AM UTC12.121 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Engine breadthEngine breadth · observed Sep 17, 2026, 12:00 AM UTC2 engines100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Mention coverageMention coverage · observed Sep 17, 2026, 12:00 AM UTC36.111 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Reviewed-brand presence shareMention share · observed Sep 17, 2026, 12:00 AM UTC15.294 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Recommendation-prompt presenceRecommendation presence · observed Sep 17, 2026, 12:00 AM UTC41.667 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini citation shareGemini brand citation share · observed Sep 17, 2026, 12:00 AM UTC26.667 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini mention coverageGemini brand mention coverage · observed Sep 17, 2026, 12:00 AM UTC66.667 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 17, 2026, 12:00 AM UTC75 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI citation shareOpenAI brand citation share · observed Sep 17, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI mention coverageOpenAI brand mention coverage · observed Sep 17, 2026, 12:00 AM UTC41.667 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI recommendation-prompt presenceOpenAI brand recommendation presence · observed Sep 17, 2026, 12:00 AM UTC50 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Cite this data

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Plain textCloud GPU platforms engine breadth. Rank.ai, data as of September 17, 2026. https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-engine-breadth
HTML<a href="https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-engine-breadth">Cloud GPU platforms engine breadth</a>, Rank.ai, data as of September 17, 2026
Markdown[Cloud GPU platforms engine breadth](https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-engine-breadth), Rank.ai, data as of September 17, 2026
APARank.ai. (2026). Cloud GPU platforms engine breadth. Retrieved October 22, 2026, from https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-engine-breadth

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<iframe src="https://www.rank.ai/embed/boards/cloud-gpu-platforms-brand-engine-breadth" title="Cloud GPU platforms engine breadth" width="100%" height="420" loading="lazy" style="border:1px solid #111;max-width:720px"></iframe>
<p style="font-size:12px">Source: <a href="https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-engine-breadth">Cloud GPU platforms engine breadth</a> by Rank.ai</p>

More in Cloud GPU platforms

Specialist GPU clouds, marketplaces, and hyperscalers ranked across a fixed infrastructure buying corpus, with brand, prompt, engine and citation source views.

3 boards

Cloud GPU platform rank

Reviewed GPU infrastructure providers ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

1Runpod58.3%
2Lambda Cloud250%
3Google Cloud141.7%

Cloud GPU platform presence

Reviewed providers ranked by the share of all the category's answers that name or cite them.

1Runpod44.4%
2Lambda Cloud238.9%
3Google Cloud136.1%

Cloud GPU platform citation share

Reviewed providers ranked by distinct answer-level citations to their canonical domains.

1Runpod42.4%
2Lambda Cloud27.3%
3Google Cloud12.1%

Cloud GPU platform rank

Reviewed GPU infrastructure providers ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Cloud GPU platform presence

Reviewed providers ranked by the share of all the category's answers that name or cite them.

Cloud GPU platform citation share

Reviewed providers ranked by distinct answer-level citations to their canonical domains.

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Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
Who gets namedEvery competitor in the answers, most named first.
The pages AI readsThe sources behind each answer.
Three fixesWhat to fix first, with a brief for the first article.

Cloud GPU platforms engine breadth

All 16 companies by engine breadth

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

Google Cloud on Cloud GPU Platforms Engine Breadth

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More in Cloud GPU platforms

See how often AI names you.

One brand against up to three competitors, answer by answer

Which compared brands each answer names

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