AI visibility report
Beam ranks #3 in LLM Inference & Serverless GPU AI search.
Outside the top three on 17 of the 25 prompts buyers actually ask.
Baseten is cited on 7 of those losses.
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Track Beam across these prompts daily.
Start free trial#3 among 10 vendors · still absent from 88.8% of tracked prompt responses
Top-3 citations across 125 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Perplexity
ChatGPT
Bing Copilot
Google AI Mode
Gemini SearchVisible, but narrative can improve. Beam ranks #3 on presence but #7 on sentiment. The brand appears relatively often, but competitors may be getting more favorable language when they appear.
Where Beam is losing
Prompts where competitors are visible and Beam is not.
These prompt-level losses are the first prompts to track and repair.
Where Beam is winning1
What LLM inference platforms offer the best SDK and API ergonomics for a Python-first engineering team shipping a conversational AI feature?
Avg # 1.0 · 1 platform
Where Beam is losing5
Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying?
Competitors on 3 platforms
Track this promptWhich LLM inference platforms integrate natively with vector database services for building retrieval-augmented generation pipelines without extra glue code?
Competitors on 2 platforms
Track this promptWhat 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?
Competitors on 2 platforms
Track this promptWhich LLM inference platforms have the easiest onboarding for a solo developer deploying a fine-tuned open-source model for the first time?
Competitors on 2 platforms
Track this promptWhich LLM inference platforms support deploying quantized open-source models with minimal setup for a backend engineer with no MLOps background?
Competitors on 2 platforms
Track this prompt
Track Beam daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
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.
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 Facts
- Founded
- 2021
- HQ
- New York, NY, USA
- Founders
- Eli Mernit, Luke Lombardi
- Employees
- 5-10
- Funding
- $7M
- Customers
- hundreds (self-reported)
- Status
- Private
Target users
Key Capabilities10
- 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
Key Use Cases8
- 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
Beam customer outcomes
Hours vs. weeks to build GPU app component
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.
Coca-Cola is cited as a production customer using Beam for serverless GPU inference workloads at enterprise scale.
Recent Trend
How AI describes Beam3
Direct answer: RunPod, Modal, Replicate, and Beam are commonly cited as serverless GPU platforms with built‑in observability for latency and throughput, though the exact per-request latency and token throughput visibility out of the box can vary by provi...
Which serverless GPU platforms give engineering teams the most visibility into per-request latency and token throughput right out of the box?
Direct answer: Based on recent comparisons, Beam and RunPod tend to have the strongest claims for the lowest cold-start latency among serverless GPU inference options, with Beam often highlighted for fastest boots and RunPod offering very fast sub-second...
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?
Short answer: Modal, Replicate, RunPod, Baseten, and Beam/Mystic (and similar serverless GPU platforms) tend to offer strong developer experiences for rapid prompt/template iteration without redeploys, thanks to REST/SDK access, fast cold starts, and fle...
Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying?
Most cited sources4
Alternatives in LLM Inference & Serverless GPU6
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.
Reviews
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
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.
Pricing
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.
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.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | ChatGPT | Google AI Mode | Gemini Search | Bing Copilot | Perplexity |
|---|---|---|---|---|---|
Capability2/5 cited (40%) | |||||
What LLM inference platforms handle streaming token responses well and support long context windows for document-processing use cases? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which LLM inference platforms let enterprise teams bring their own fine-tuned model weights and enforce strict data isolation with private deployments? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which serverless inference platforms support running large multimodal models — handling both text and image inputs — on high-end GPUs at production scale? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which serverless GPU platforms support batch inference jobs for offline processing pipelines in addition to real-time API endpoints? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Your brand was cited | Your brand and a competitor were cited |
I'm looking for an inference platform that supports custom CUDA kernels and speculative decoding — what are my options for a performance-critical chatbot? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Developer Experience3/5 cited (60%) | |||||
Which serverless GPU platforms give engineering teams the most visibility into per-request latency and token throughput right out of the box? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
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? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What LLM inference platforms offer the best SDK and API ergonomics for a Python-first engineering team shipping a conversational AI feature? | A competitor was cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which serverless inference platforms make it easiest to manage multiple open-source model versions in parallel across staging and production environments? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which serverless GPU inference platforms have the best developer experience for iterating quickly on prompt templates and sampling parameters without redeploying? | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Integrations & Ecosystem1/5 cited (20%) | |||||
Which LLM inference platforms integrate natively with vector database services for building retrieval-augmented generation pipelines without extra glue code? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What serverless GPU inference providers work best alongside AI orchestration frameworks so teams can chain model calls and tool use cleanly? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which inference platforms expose an API compatible with the standard chat completions format so switching providers requires minimal code changes? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What LLM inference platforms integrate with cloud object storage for loading large model weights at deploy time without manual upload steps? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which serverless GPU platforms support webhook callbacks or event-driven triggers for async inference jobs in a data pipeline built on a workflow orchestrator? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Performance & Reliability2/5 cited (40%) | |||||
Which serverless inference providers deliver the highest tokens-per-second throughput for a high-volume API serving thousands of concurrent users? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
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? | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Your brand was cited |
What are the most reliable LLM serving platforms for an enterprise use case that requires 99.9% uptime SLAs and geo-redundant deployments? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What LLM inference platforms can handle sudden traffic spikes — say 10x burst load — without throttling for a mid-sized SaaS product? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which serverless GPU platforms have the best cost-per-token at scale for a startup burning significant GPU budget on a document summarization product? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Setup & First Run3/5 cited (60%) | |||||
Which LLM inference platforms have the easiest onboarding for a solo developer deploying a fine-tuned open-source model for the first time? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which LLM inference platforms support deploying quantized open-source models with minimal setup for a backend engineer with no MLOps background? | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What's the quickest serverless GPU platform to get an image-generation model behind a REST API with autoscaling out of the box? | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
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? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited |
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? | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | RunPod | 15.2% | 29.5% | 1.6% | 0.0% | 40.0% | #4.2 | +0.32 |
| 2 | Fireworks AI | 12.0% | 17.0% | 1.6% | 6.4% | 36.8% | #3.4 | +0.46 |
| 3 | Beam | 11.2% | 17.9% | 0.0% | 0.0% | 12.0% | #4.8 | +0.29 |
| 4 | Baseten | 8.8% | 16.1% | 6.4% | 3.2% | 42.4% | #2.6 | +0.50 |
| 5 | Modal | 8.0% | 9.8% | 0.0% | 2.4% | 0.0% | #3.2 | +0.55 |
| 6 | Together AI | 5.6% | 7.1% | 2.4% | 0.8% | 44.8% | #2.1 | +0.30 |
| 7 | Cerebrium | 2.4% | 2.7% | 0.8% | 0.0% | 8.0% | #2.0 | +0.60 |
| 8 | Lepton AI | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 9 | Replicate | 0.0% | 0.0% | 0.0% | 0.0% | 32.8% | — | — |
| 10 | Sference | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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