GPU clouds in OpenAI model API answers

As of

All 16 companies by OpenAI recommendation prompt presence

Runpod leads at 87.5%; the middle of the board sits at 12.5%.

Ahead of second place: 12.5%
Held by the top three: 54%
Middle of the board: 12.5%
Below half the leader: 10 of 16

Rank, name and OpenAI recommendation prompt presenceMiddle 12.5%

1Runpod87.5%
2Lambda Cloud75.0%
3CoreWeave75.0%
4Google Cloud50.0%
5Microsoft Azure50.0%
6Vast.ai50.0%
7Paperspace12.5%
8Hyperstack12.5%
9IBM Cloud12.5%
10Nebius AI Cloud12.5%
11Crusoe Cloud0.0%
12Amazon EC20.0%
13Oracle Cloud Infrastructure0.0%
14Akash Network0.0%
15Fluidstack0.0%
16Voltage Park0.0%

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.

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

Cloud GPU platforms brands in OpenAI model API answers current rankings
Rank	Name	OpenAI recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	Runpod	87.5%	44.44% · 16 / 36	18.82% · 16 / 85	42.42% · 14 / 33		This rank My rank
02	Lambda Cloud	75.0%	38.89% · 14 / 36	16.47% · 14 / 85	27.27% · 9 / 33	3	This rank My rank
03	CoreWeave	75.0%	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33	1	This rank My rank
04	Google Cloud	50.0%	36.11% · 13 / 36	15.29% · 13 / 85	12.12% · 4 / 33	2	This rank My rank
05	Microsoft Azure	50.0%	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33	2	This rank My rank
06	Vast.ai	50.0%	22.22% · 8 / 36	9.41% · 8 / 85	0% · 0 / 33		This rank My rank
07	Paperspace	12.5%	11.11% · 4 / 36	4.71% · 4 / 85	6.06% · 2 / 33	8	This rank My rank
08	Hyperstack	12.5%	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	1	Showing My rank
09	IBM Cloud	12.5%	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	1	This rank My rank
10	Nebius AI Cloud	12.5%	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33		This rank My rank
11	Crusoe Cloud	0.0%	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33	4	This rank My rank
12	Amazon EC2	0.0%	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
13	Oracle Cloud Infrastructure	0.0%	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
14	Akash Network	0.0%	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
15	Fluidstack	0.0%	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
16	Voltage Park	0.0%	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33		This rank My rank

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

Cloud GPU platforms brands in OpenAI model API answers current rankings
Rank	Name	OpenAI recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	Runpod	87.5%	44.44% · 16 / 36	18.82% · 16 / 85	42.42% · 14 / 33		This rank My rank
02	Lambda Cloud	75.0%	38.89% · 14 / 36	16.47% · 14 / 85	27.27% · 9 / 33	3	This rank My rank
03	CoreWeave	75.0%	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33	1	This rank My rank
04	Google Cloud	50.0%	36.11% · 13 / 36	15.29% · 13 / 85	12.12% · 4 / 33	2	This rank My rank
05	Microsoft Azure	50.0%	30.56% · 11 / 36	12.94% · 11 / 85	0% · 0 / 33	2	This rank My rank
06	Vast.ai	50.0%	22.22% · 8 / 36	9.41% · 8 / 85	0% · 0 / 33		This rank My rank
07	Paperspace	12.5%	11.11% · 4 / 36	4.71% · 4 / 85	6.06% · 2 / 33	8	This rank My rank
08	Hyperstack	12.5%	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	1	Showing My rank
09	IBM Cloud	12.5%	5.56% · 2 / 36	2.35% · 2 / 85	3.03% · 1 / 33	1	This rank My rank
10	Nebius AI Cloud	12.5%	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33		This rank My rank
11	Crusoe Cloud	0.0%	2.78% · 1 / 36	1.18% · 1 / 85	3.03% · 1 / 33	4	This rank My rank
12	Amazon EC2	0.0%	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
13	Oracle Cloud Infrastructure	0.0%	2.78% · 1 / 36	1.18% · 1 / 85	0% · 0 / 33	1	This rank My rank
14	Akash Network	0.0%	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
15	Fluidstack	0.0%	0% · 0 / 36	0% · 0 / 85	0% · 0 / 33	2	This rank My rank
16	Voltage Park	0.0%	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.

8

Rank on this board

12.5 percent

Score

8

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 Hyperstack's score
Component	Value	Contribution
OpenAI brand recommendation presence	12.5	12.5

Moved up since the previous snapshot

+1 places

OpenAI brand recommendation presence0 to 12.5
+12.5
OpenAI brand citation share0 to 8.333
+8.333
OpenAI brand mention coverage0 to 8.333
+8.333
Recommendation presence4.167 to 8.333
+4.167
Citation share0 to 3.03
+3.03
Mention coverage2.778 to 5.556
+2.778
Engine breadth1 to 2
+1
Mention share1.563 to 2.353
+0.79
Anthropic brand mention coverage0 to 0
0
Anthropic brand recommendation presence0 to 0
0
Gemini brand citation share0 to 0
0
Gemini brand mention coverage8.333 to 8.333
0
Gemini brand recommendation presence12.5 to 12.5
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
{"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 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 UTC3.03 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 UTC5.556 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 UTC2.353 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 UTC8.333 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 UTC0 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 UTC8.333 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 17, 2026, 12:00 AM UTC12.5 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 UTC8.333 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 UTC8.333 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 UTC12.5 percent100% confidence
Source
Rank.ai Cloud GPU Platforms Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Plain textCloud GPU platforms brands in OpenAI model API answers. Rank.ai, data as of September 17, 2026. https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-openai-visibility
HTML<a href="https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-openai-visibility">Cloud GPU platforms brands in OpenAI model API answers</a>, Rank.ai, data as of September 17, 2026
Markdown[Cloud GPU platforms brands in OpenAI model API answers](https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-openai-visibility), Rank.ai, data as of September 17, 2026
APARank.ai. (2026). Cloud GPU platforms brands in OpenAI model API answers. Retrieved October 22, 2026, from https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-openai-visibility

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<p style="font-size:12px">Source: <a href="https://www.rank.ai/rankings/cloud-gpu-platforms/cloud-gpu-platforms-brand-openai-visibility">Cloud GPU platforms brands in OpenAI model API answers</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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Cloud GPU platforms brands in OpenAI model API answers

All 16 companies by OpenAI recommendation prompt presence

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

Hyperstack on Cloud GPU Platforms Brands in OpenAI Model API Answers

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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

The sites these answers cite