# Beam AI visibility in LLM Inference & Serverless GPU

Canonical: https://devtune.ai/verticals/llm-inference-serverless-gpu/beam

[Website](https://beam.cloud/)

Updated: 2026-10-20T01:11:02.395032+00:00
Prompts: 25
Runs: 5


## Platforms

- google-ai-mode
- perplexity
- bing-copilot-search
- google-ai
- chatgpt-search

Rank: 8
Total brands: 10
Measured responses: 125
Presence percent: 4
Share of voice percent: 3.0927835051546393
Average position: 14.222222222222221
Docs presence percent: 0
Blog presence percent: 0
Brand mention percent: 11.200000000000001


## Profile

Overview: Beam (beam.cloud) is an open-source, serverless AI infrastructure platform founded in 2021 and backed by Y Combinator (W22), Tiger Global, and angel investors including the founders of Snyk and GitHub. Built around a custom container runtime called beta9, Beam enables developers to run GPU inference endpoints, secure code sandboxes, async task queues, and scheduled jobs using simple Python or TypeScript decorators—with no YAML or Dockerfile configuration required. Containers launch in under one second, billing is per-millisecond, and apps scale to zero when idle. Beam differentiates as the only major serverless GPU platform with a fully open-source, self-hostable runtime (AGPL-3.0), enabling deployment across Beam's managed cloud, AWS, or on-premises infrastructure. Named customers include Coca-Cola, Magellan AI, Geospy, and Frase.
Product summary: Beam is an open-source serverless cloud platform for AI inference, sandboxes, and background jobs. Developers decorate Python or TypeScript functions to run on GPU or CPU-backed containers that launch in under one second, autoscale to thousands of replicas, and bill only for active compute time. The platform supports REST endpoint deployment, async task queues, scheduled cron jobs, sandbox environments with checkpoint/restore for long-running agent sessions, and self-hosting via its open-source runtime (beta9). It is used by startups and Fortune 100 companies to run custom ML models and execute LLM-generated code securely at scale.


### Key capabilities

- Serverless GPU and CPU inference endpoints with pay-per-millisecond billing
- Sub-second container launch via custom Go-based runtime (beta9)
- Secure LLM-generated code execution in gVisor-isolated sandboxes
- Sandbox snapshots and GPU checkpoint/restore for stateful agent sessions
- Async task queues and scheduled cron jobs with no timeouts
- Instant autoscaling to thousands of containers with scale-to-zero
- Open-source, self-hostable runtime (AGPL-3.0) deployable on AWS or local machine
- Distributed storage volumes and S3 bucket mounting
- Python and TypeScript SDKs with decorator-based deployment (no YAML required)
- CI/CD integration via GitHub Actions and versioned endpoint deployments



### Target users

- AI/ML engineers deploying custom inference endpoints
- Full-stack developers building generative AI products
- AI agent developers needing secure code sandbox execution
- DevOps and platform teams requiring self-hostable GPU infrastructure
- Startups and scale-ups running bursty or variable GPU workloads
- Enterprise teams seeking portable, cloud-agnostic AI compute



### Key use cases

- Serverless GPU inference for custom ML and generative AI models
- Secure code sandbox execution for AI agents and LLM-generated code
- Async background batch processing and data pipelines on GPU/CPU
- Scheduled ML training jobs and distributed function execution
- Rapid deployment of Dockerized AI models as REST APIs
- Hybrid cloud and on-premises AI workloads requiring self-hosting
- Image generation and video transcription services with autoscaling
- Conversational AI and LLM endpoint hosting for production apps

Integrations ecosystem: Beam provides a Python SDK (pip install beam-client) and a TypeScript/JavaScript SDK (beta). The CLI supports CI/CD integration via GitHub Actions. Container images can be pulled from custom Docker registries. External cloud storage is supported via S3 bucket mounting. Distributed storage volumes are built in. Sandboxes use gVisor for isolation. Jupyter Notebook support is available for interactive development. The open-source runtime (beta9, Go, AGPL-3.0, ~1.6k GitHub stars) supports self-hosting on AWS or local machines. No native integrations with MLflow, Weights & Biases, or model-registry platforms were documented at time of research.
Pricing summary: Beam uses pay-per-millisecond billing with no upfront commitments. Published rates: CPU at $0.190/core/hr, RAM at $0.020/GB/hr, RTX 4090 at $0.69/hr, A10G at $1.05/hr, H100 at $3.50/hr. File storage is included at no charge. Cold start time (container spin-up) is not billed. New accounts receive 15 hours of free credit on signup. Beam claims up to 80% savings versus always-on VM instances for bursty workloads. No tiered plan structure or minimum spend requirement is documented; enterprise pricing is available via direct contact.
Review summary: Public developer sentiment is broadly positive, with users citing fast onboarding, strong developer experience, and elimination of VM management overhead. Testimonials highlight the ability to ship GPU-backed features in hours rather than weeks, and praise the responsiveness of the Beam team. Third-party comparison analyses position Beam as the preferred choice for teams requiring portability and self-hosting, while noting that cold start times (2–3 seconds) lag behind Modal's sub-second performance and that the GPU catalog is narrower than RunPod's. No formal review scores from G2, Gartner Peer Insights, or Capterra were found at time of research.
Competitive positioning: Beam positions itself explicitly as an open-source alternative to Modal, differentiating through its self-hostable runtime (beta9, AGPL-3.0), portable workloads across cloud and on-premises, and a Python/TypeScript decorator-based developer experience requiring no YAML or Dockerfile configuration. Its primary wedge is vendor-lock-in avoidance: the same CLI and SDK work identically on Beam cloud, AWS self-hosted, or a local machine. Beam targets AI teams building bursty inference, agent sandboxes, and background jobs who want serverless economics without proprietary platform dependency. Compared to Modal (developer experience, closed), RunPod (price/GPU breadth, closed), and Baseten (enterprise inference, closed), Beam is the only OSS-first, self-hostable option in the segment.
Limitations: Cold start times of 2–3 seconds cited by third-party comparisons for most workloads, slower than Modal's sub-second Rust-based runtime. GPU catalog is narrower than RunPod (T4, RTX 4090, A10G, A100, H100 listed; no H200 or B200 published). No formal enterprise SLAs or uptime guarantees documented publicly (unlike Baseten's 99.99%). Very small team (approximately 5–7 people) may limit enterprise support and feature velocity. No egress-free regions noted (unlike RunPod). TypeScript SDK remains in beta. No published model marketplace or pre-hosted foundation model library. Limited geographic region information disclosed. No SOC 2 certification publicly confirmed at time of research.


### Source urls

- https://beam.cloud/
- https://docs.beam.cloud/v2/getting-started/introduction
- https://docs.beam.cloud/v2/resources/pricing-and-billing
- https://www.ycombinator.com/companies/beam
- https://github.com/beam-cloud
- https://github.com/beam-cloud/beta9
- https://getdeploying.com/beam
- https://tracxn.com/d/companies/beam/__QoLpZHNElS_6QKeshaFPksdNskJ4RXD5XMvgC1HJL-k
- https://introl.com/blog/serverless-gpu-platforms-runpod-modal-beam-comparison-guide-2025
- https://cloudgpuprices.com/vendors/beam
- https://www.ycombinator.com/companies/beam/jobs/6rKakUF-growth

Reviewed at: 2026-05-06T17:53:53.835+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| Happy Accidents | The team credited Beam with enabling them to ship their product significantly faster than expected, building the GPU-powered portion of their application in hours rather than weeks. | Hours vs. weeks to build GPU app component |
| Coca-Cola | Coca-Cola is cited as a production customer using Beam for serverless GPU inference workloads at enterprise scale. | Not available |



### Reviews breakdown





### Review themes



#### Praised

- Excellent developer experience and onboarding
- Fast GPU deployment with minimal configuration
- Pay-per-millisecond billing reduces idle compute costs
- Highly responsive founder/support team
- Open-source and self-hostable runtime
- Eliminates VM infrastructure management overhead
- Python decorator-based API requires no YAML or Dockerfiles



#### Criticized

- Cold starts (2–3s) slower than Modal's sub-second performance
- Narrower GPU catalog compared to RunPod
- Small team may limit enterprise support capacity
- TypeScript SDK still in beta
- No publicly confirmed SOC 2 or formal enterprise SLA
- Limited published information on geographic regions




### Company facts

Founded year: 2021
Hq: New York, NY, USA


#### Founders

- Eli Mernit
- Luke Lombardi

Employees range: 5-10
Total funding: $7M
Valuation: Not available
Arr: Not available
Customer count: hundreds (self-reported)
Status: Private


Readiness: Not available


## Ranking

| Display name | Pair count | Total pairs | Presence percent | Avg position |
| --- | --- | --- | --- | --- |
| Modal | 37 | 125 | 29.599999999999998 | 8.035714285714286 |
| RunPod | 24 | 125 | 19.2 | 4.56 |
| Baseten | 19 | 125 | 15.2 | 5.681818181818182 |
| Fireworks AI | 15 | 125 | 12 | 6.818181818181818 |
| Together AI | 14 | 125 | 11.200000000000001 | 4.96875 |
| Cerebrium | 12 | 125 | 9.6 | 5.142857142857143 |
| Replicate | 11 | 125 | 8.799999999999999 | 16.24137931034483 |
| Beam | 5 | 125 | 4 | 14.222222222222221 |
| Lepton AI | 0 | 125 | 0 | Not available |
| Sference | 0 | 125 | 0 | Not available |



## Platform breakdown

| Platform | Prompt count | Presence rate |
| --- | --- | --- |
| google-ai-mode | 0 | 0 |
| perplexity | 1 | 4 |
| bing-copilot-search | 2 | 8 |
| google-ai | 0 | 0 |
| chatgpt-search | 2 | 8 |



## Strengths

| Prompt text | Platform count | Avg position |
| --- | --- | --- |
| I'm evaluating serverless inference platforms for a small startup — which ones let you deploy a custom open-source LLM without writing any infrastructure config? | 1 | 1 |



## Gaps

| Prompt text | Competitor presence count |
| --- | --- |
| Which serverless inference platforms support running large multimodal models — handling both text and image inputs — on high-end GPUs at production scale? | 4 |
| What serverless GPU inference providers work best alongside AI orchestration frameworks so teams can chain model calls and tool use cleanly? | 4 |
| Which serverless GPU platforms support webhook callbacks or event-driven triggers for async inference jobs in a data pipeline built on a workflow orchestrator? | 4 |
| What's the quickest serverless GPU platform to get an image-generation model behind a REST API with autoscaling out of the box? | 4 |
| Which LLM inference platforms have the easiest onboarding for a solo developer deploying a fine-tuned open-source model for the first time? | 3 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 1 |
| Developer Experience | 5 | 0 |
| Integrations & Ecosystem | 5 | 1 |
| Performance & Reliability | 5 | 1 |
| Setup & First Run | 5 | 1 |



## Prompt results

- Prompt text: Which LLM inference platforms have the easiest onboarding for a solo developer deploying a fine-tuned open-source model for the first time?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Together AI | 1 |
| Replicate | 5 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Together AI | 2 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Replicate | 2 |


- Prompt text: What are the fastest serverless GPU inference platforms to go from an open-source LLM to a live production API endpoint with no GPU infrastructure to manage?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 2 |
| Cerebrium | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Modal | 4 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 2 |
| Fireworks AI | 4 |
| Together AI | 5 |


- Prompt text: What LLM inference platforms handle streaming token responses well and support long context windows for document-processing use cases?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Fireworks AI | 2 |
| Together AI | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Together AI | 2 |
| Fireworks AI | 6 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Cerebrium | 8 |
| Fireworks AI | 11 |


- Prompt text: Which LLM inference platforms let enterprise teams bring their own fine-tuned model weights and enforce strict data isolation with private deployments?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 6 |



##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 4 |
| Together AI | 7 |
| Fireworks AI | 12 |


- Prompt text: Which serverless inference platforms support running large multimodal models — handling both text and image inputs — on high-end GPUs at production scale?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 2 |
| Together AI | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Modal | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 2 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Cerebrium | 4 |
| Modal | 5 |
| Baseten | 6 |
| Fireworks AI | 10 |


- Prompt text: I'm evaluating serverless inference platforms for a small startup — which ones let you deploy a custom open-source LLM without writing any infrastructure config?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: 1
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Together AI | 1 |
| Fireworks AI | 3 |
| Baseten | 4 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Replicate | 1 |
| Baseten | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Beam | 1 |
| Modal | 2 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 1 |
| Fireworks AI | 9 |


- Prompt text: What LLM inference platforms can handle sudden traffic spikes — say 10x burst load — without throttling for a mid-sized SaaS product?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 3 |
| Together AI | 5 |



##### Perplexity





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| RunPod | 3 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Together AI | 1 |
| Fireworks AI | 6 |


- Prompt text: Which serverless inference platforms make it easiest to manage multiple open-source model versions in parallel across staging and production environments?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Cerebrium | 4 |
| Modal | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Replicate | 3 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Modal | 4 |
| Replicate | 14 |
| Baseten | 15 |


- Prompt text: What serverless GPU inference providers work best alongside AI orchestration frameworks so teams can chain model calls and tool use cleanly?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 1 |
| Cerebrium | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 2 |
| Modal | 8 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 3 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Fireworks AI | 1 |


- Prompt text: Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 1 |



##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Replicate | 3 |
| Baseten | 5 |


- Prompt text: Which serverless GPU platforms support batch inference jobs for offline processing pipelines in addition to real-time API endpoints?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: 1
Google-ai: Not available
Chatgpt-search: 5



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 5 |
| Baseten | 9 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Beam | 1 |
| Modal | 2 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 3 |
| Beam | 5 |
| Baseten | 13 |
| Replicate | 14 |


- Prompt text: Which inference platforms expose an API compatible with the standard chat completions format so switching providers requires minimal code changes?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search




- Prompt text: What LLM inference platforms integrate with cloud object storage for loading large model weights at deploy time without manual upload steps?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Cerebrium | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Modal | 1 |
| RunPod | 5 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Cerebrium | 4 |



##### Google-ai





##### Chatgpt-search




- Prompt text: Which serverless GPU platforms have the best cost-per-token at scale for a startup burning significant GPU budget on a document summarization product?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Fireworks AI | 2 |
| Cerebrium | 3 |
| RunPod | 5 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 3 |
| Together AI | 4 |
| Fireworks AI | 5 |
| Baseten | 6 |


- Prompt text: What are the best LLM serving platforms for a small ML team that needs built-in request logging and usage dashboards without wiring up a separate observability stack?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity

| Display name | Position |
| --- | --- |
| Replicate | 3 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Modal | 3 |
| RunPod | 6 |


- Prompt text: I'm looking for an inference platform that supports custom CUDA kernels and speculative decoding — what are my options for a performance-critical chatbot?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search




- Prompt text: Which serverless GPU platforms support webhook callbacks or event-driven triggers for async inference jobs in a data pipeline built on a workflow orchestrator?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: 41



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Baseten | 3 |
| Cerebrium | 6 |
| Modal | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 2 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 2 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Replicate | 9 |
| RunPod | 10 |
| Modal | 12 |
| Beam | 41 |


- Prompt text: Which LLM inference platforms support deploying quantized open-source models with minimal setup for a backend engineer with no MLOps background?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 6 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Together AI | 3 |
| Fireworks AI | 5 |
| RunPod | 6 |
| Modal | 8 |


- Prompt text: What LLM inference platforms offer the best SDK and API ergonomics for a Python-first engineering team shipping a conversational AI feature?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity

| Display name | Position |
| --- | --- |
| Together AI | 6 |
| Fireworks AI | 7 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Together AI | 3 |
| Fireworks AI | 7 |


- Prompt text: What's the quickest serverless GPU platform to get an image-generation model behind a REST API with autoscaling out of the box?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Modal | 2 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Replicate | 1 |
| Modal | 4 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Modal | 2 |



##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Replicate | 1 |
| Modal | 3 |
| RunPod | 4 |


- Prompt text: Which serverless GPU platforms give engineering teams the most visibility into per-request latency and token throughput right out of the box?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Cerebrium | 5 |
| Modal | 9 |



##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Baseten | 1 |
| Modal | 3 |
| RunPod | 4 |


- Prompt text: Which serverless inference providers deliver the highest tokens-per-second throughput for a high-volume API serving thousands of concurrent users?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search




- Prompt text: What are the most reliable LLM serving platforms for an enterprise use case that requires 99.9% uptime SLAs and geo-redundant deployments?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search




- Prompt text: Which LLM inference platforms integrate natively with vector database services for building retrieval-augmented generation pipelines without extra glue code?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode





##### Perplexity





##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search




- Prompt text: Which serverless GPU inference platforms have the lowest cold-start latency for a customer-facing chat app that needs sub-second first-token response times?


#### Brand position by platform

Google-ai-mode: Not available
Perplexity: 6
Bing-copilot-search: Not available
Google-ai: Not available
Chatgpt-search: Not available



#### Platform rows



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Cerebrium | 1 |
| RunPod | 4 |



##### Perplexity

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 5 |
| Beam | 6 |
| Cerebrium | 7 |



##### Bing-copilot-search





##### Google-ai





##### Chatgpt-search

| Display name | Position |
| --- | --- |
| RunPod | 1 |
| Modal | 3 |
| Baseten | 5 |





## Top sources

| Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count |
| --- | --- | --- | --- | --- | --- | --- | --- |
| https://www.beam.cloud/blog/cold-start-serverless-gpu-inference | Fast Cold Starts for Serverless GPU Inference - Beam Cloud | beam.cloud | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/16f1426c-4fe3-4ca3-83a1-36e76ba0b4b5/1c0be234f7c5b827ee6f533dad63c415d385c579.png | commercial | blog_post | 5 | 5 |
| https://www.beam.cloud/inference | Serverless Model Inference \| Beam | beam.cloud | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/16f1426c-4fe3-4ca3-83a1-36e76ba0b4b5/1c0be234f7c5b827ee6f533dad63c415d385c579.png | commercial | landing_page | 5 | 5 |
| https://www.beam.cloud/blog/serverless-gpu | AI Infrastructure For Developers | beam.cloud | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/16f1426c-4fe3-4ca3-83a1-36e76ba0b4b5/1c0be234f7c5b827ee6f533dad63c415d385c579.png | commercial | landing_page | 4 | 4 |
| https://www.beam.cloud/use-cases/batch-processing | Batch Jobs & Data Pipelines on Serverless Compute \| Beam | beam.cloud | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/16f1426c-4fe3-4ca3-83a1-36e76ba0b4b5/1c0be234f7c5b827ee6f533dad63c415d385c579.png | commercial | product_page | 3 | 3 |
| https://www.beam.cloud/blog/batch-inference-serverless-gpu | Batch Inference on Serverless GPU \| Beam | beam.cloud | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/16f1426c-4fe3-4ca3-83a1-36e76ba0b4b5/1c0be234f7c5b827ee6f533dad63c415d385c579.png | commercial | landing_page | 1 | 1 |
| https://www.beam.cloud/blog/scheduled-gpu-cron-jobs | GPU Cron Jobs: Run Scheduled Jobs on GPUs \| Beam | beam.cloud | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/16f1426c-4fe3-4ca3-83a1-36e76ba0b4b5/1c0be234f7c5b827ee6f533dad63c415d385c579.png | commercial | blog_post | 1 | 1 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| Which serverless GPU inference platforms have the lowest cold-start latency for a customer-facing chat app that needs sub-second first-token response times? | google-ai-mode | Cerebrium & Beam (The Fast Scale-to-Zero Leaders) * * Cold Start Latency: ∼2 s −4 s (scale-to-zero) [Cerebrium] * How they achieve it: They use aggressive container snapshotting, optimized network filesystems, and pre-loaded base im... |
| Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying? | google-ai-mode | ...e-tuning/eval integrations\| Rapid zero-infrastructure testing across standard open-weights models (Llama, Mistral, Qwen) Beam Cloud\| Python-script execution with instant cloud-function deployment\| Remote function execution via CLI/SDK\| Quick serve... |
| What are the fastest serverless GPU inference platforms to go from an open-source LLM to a live production API endpoint with no GPU infrastructure to manage? | google-ai-mode | [Cerebrium +1] 3. Beam Cloud * What it does: An infrastructure platform designed for deploying containerized AI workloads and serverless webhooks with minimal configuration. |



## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| google-ai-mode | RunPod | runpod.io/articles/guides/multimodal-ai-deployment-guide-running-vision-language-models)Best Serverless GPU Platforms for Inference in 2026 - Modal The top serverless inference platf... |
| google-ai-mode | Modal | Multimodal AI Deployment: VisionBest Serverless GPU Platforms for Inference in 2026 - Modal The top serverless inference platforms capable of handling custom or hosted LMM workflows on high-end GPUs at production scale include: * * * * * 1\. |
| perplexity | Modal | Modal — Offers serverless inference and high-end GPUs including H100, H200 and B200, with dynamic scaling to 1,000+ GPUs. |
| bing-copilot-search | Modal | ...p 10 AI Inference Platforms in 2026 (Compared) - OneInfer](https://oneinfer.ai/blogs/top-10-ai-inference-platforms-2026) Modal\| Code-first SDK, strong autoscaling, enterprise compliance (SOC 2, HIPAA)\| Scales from 0 → 1000+ GPUs; per-second billin... |
| chatgpt-search | RunPod | Website: baseten.co ## 3. RunPod Provides serverless GPU endpoints, autoscaling, custom workers, and vLLM deployment options. |
| google-ai-mode | Modal | * Top Serverless GPU Providers for Chained AI Workflows 1. Modal * Why it shines for orchestration: Modal allows you to define arbitrary Python functions decorated with `@app.function` that spin up instantly on serverless GPUs (from T4 to H100/B300). |
| google-ai-mode | Cerebrium | ...ying LlamaIndex agent workflows](https://modal.com/resources/best-serverless-platforms-llamaindex-agent-workflows) 2. Cerebrium * Why it shines for orchestration: Built explicitly for AI workflows, Cerebrium offers... |
| perplexity | RunPod | RunPod Serverless — A strong fit when you want to deploy your own containerized model and GPU-backed endpoint. |
| bing-copilot-search | Modal | ...ther API call Serverless GPU Cloud 2026: RunPod, Together AI, Salad Compared Modal\| Code-first deployments, fast autoscaling\| Pay-per-active GPU compute\| Strong fit for teams who want orchestration tight... |
| chatgpt-search | Fireworks AI | My shortlist is RunPod, Modal, Baseten, Replicate, and fal.ai, with Fireworks AI and Together AI especially worth considering for OpenAI-compatible, high-throughput LLM serving. |
| google-ai-mode | RunPod | Send API requests - Runpod DocumentationServerless Webhooks with Cerebrium \| Wayne Lau[Inference](https://docs.baseten.co/infere... |
| google-ai-mode | Baseten | baseten.co/inference/overview)Using asynchronous inference in productionAsync inferenceAsync requests - Cerebrium Several major serverless GPU providers natively support webhook callbacks or event-driven async patterns suited for orchestration pipelines: 1\. |



## Trend

Visibility delta: 1.5
Avg position delta: 11.222222222222221
Citation count delta: 7