AI visibility report for Cerebrium
Vertical: LLM Inference & Serverless GPU
AI search visibility benchmark across 3 platforms in LLM Inference & Serverless GPU.
Presence Rate
Top-3 citations across 75 prompt × platform pairs
Sentiment
Peer Ranking
Key Metrics
Platform Breakdown
Perplexity
ChatGPT
Gemini SearchOverview
Cerebrium is a New York-based serverless AI infrastructure platform founded in 2021 and backed by Gradient Ventures, Y Combinator, and Authentic Ventures. The platform enables engineering teams to deploy, scale, and operate multimodal AI workloads—including LLMs, voice agents, video generation, and digital avatars—without managing servers or DevOps infrastructure. Cerebrium's core technical differentiator is its proprietary container runtime with GPU and memory snapshotting, delivering cold starts of 2–4 seconds across 12+ GPU types from T4 to B200. It charges per second of actual compute usage, supports custom Dockerfiles without code rewrites, and provides native multi-region deployment, OpenTelemetry observability, and enterprise compliance certifications (SOC 2, HIPAA, GDPR, ISO 27001). Notable customers include Tavus, Deepgram, Vapi, and Resemble AI.
Cerebrium is a managed serverless GPU platform for real-time, multimodal AI applications. It allows developers to deploy any AI workload—LLMs, voice pipelines, video models, or custom containers—using a simple CLI or Dockerfile, with automatic autoscaling, per-second billing, and built-in observability across multiple cloud regions.
Key Facts
- Founded
- 2021
- HQ
- New York, USA
- Founders
- Michael Louis, Jonathan Irwin
- Employees
- 11-50
- Funding
- ~$9M
- Status
- Private
Target users
Key Capabilities10
- Serverless GPU compute with 2–4 second cold starts via memory and GPU snapshotting
- 12+ GPU types (T4, L4, A10, L40s, A100 40/80GB, H100, H200, B200) with per-second billing
- Bring-your-own-Dockerfile deployment with no SDK rewrites or decorators required
- Elastic autoscaling from zero to thousands of concurrent GPU instances
- Multi-region deployments (US, EU, Asia) with data residency and sovereignty controls
- Full observability: real-time logs, metrics, scaling events, and native OpenTelemetry integration
- SOC 2, HIPAA, GDPR, and ISO 27001 compliance with gVisor container isolation
- WebSocket, streaming, async, and REST endpoint types with concurrency and batching controls
- CI/CD pipeline integration with gradual rollouts and versioned deployments
- 99.999% uptime with multi-region failover and automatic traffic rerouting
Key Use Cases8
- Real-time voice agent infrastructure (sub-500ms end-to-end latency pipelines)
- LLM inference serving (custom and open-source models at scale)
- LLM fine-tuning on multi-GPU clusters (H100, H200)
- Generative video and digital avatar rendering
- Image generation and computer vision inference
- Large-scale batch data processing and ETL pipelines
- Multimodal AI application pipelines combining ASR, LLMs, and TTS
- Regulated-industry AI deployments requiring HIPAA/GDPR compliance
Cerebrium customer outcomes
18x faster cold starts (from several minutes to ~10 seconds)
Migrated from multi-cloud GPU setup to Cerebrium for AI tutor and avatar workloads, eliminating complex scaling logic and allowing engineers to focus on product development.
50% lower inference costs; accuracy improved from 83% to 92%
Deployed customer-specific SLM inference at up to 150 requests/second per model with production-grade autoscaling, reducing costs while improving model accuracy.
Cold starts reduced from 30s to under 3s (warm); $5K–$10K/month in infrastructure savings
Replaced Azure Functions and reserved instances with Cerebrium for digital human avatar deployments, cutting cold-start times dramatically and eliminating idle infrastructure costs.
Runs real-time audio and video AI models at scale on Cerebrium, maintaining compute reliability through rapid viral growth and usage spikes.
Recent Trend
How AI describes Cerebrium2
Serverless GPU platforms with proven scalability for high-traffic AI apps include Google Cloud Vertex AI (with serverless inference endpoints), RunPod, Replicate, Baseten, and Cerebrium’s deployments on cloud GPUs.
Which serverless GPU platforms have proven track records with high-traffic AI applications?
Market options like Cerebrium, Mystic, and RunPod, which advertise fast spin-up, serverless-like usage, and GPU autoscaling, though specific cold-start numbers vary by setup.
Which LLM inference providers have the lowest cold start times for serverless GPU workloads?
Most cited sources2
Alternatives in LLM Inference & Serverless GPU6
Cerebrium positions itself as a developer-first, multimodal serverless GPU platform purpose-built for real-time AI workloads—voice agents, LLMs, video generation, and digital avatars—rather than a general-purpose GPU marketplace or a model-API aggregator.
- Its key differentiators are sub-4-second cold starts enabled by a proprietary container runtime and GPU/memory snapshotting, bring-your-own-Dockerfile deployment (no SDK rewrites), per-second billing, and a compliance stack (SOC 2, HIPAA, GDPR, ISO 27001) that supports enterprise data-residency requirements.
- Against Modal Labs and Beam, Cerebrium emphasizes multimodal/voice-video specialization and deeper compliance.
- Against Baseten and Replicate, it highlights full Dockerfile control and broader GPU diversity.
- Against RunPod and Together AI, it stresses managed orchestration and 99.999% uptime SLAs over raw GPU access or hosted-model APIs.
Reviews
Praised
- Sub-4 second cold starts via GPU snapshotting
- Bring-your-own-Dockerfile with no code rewrites
- Highly responsive engineering support via Slack
- 40% cost savings vs traditional cloud providers
- 12+ GPU types with per-second billing
- Production-grade autoscaling from zero to thousands of instances
- Developer-friendly CLI and deployment experience
- SOC 2, HIPAA, GDPR, ISO 27001 compliance out of the box
Criticized
- AWS and GCP credits cannot be applied to Cerebrium spend
- Not cost-optimal for always-on, high-utilization workloads
- No verified third-party reviews on G2 or Gartner (early-stage brand recognition)
- Capacity guarantees require minimum monthly spend commitments
No verified third-party review scores exist on G2 (profile unclaimed, 0 reviews) or Gartner Peer Insights as of May 2026. Community sentiment on Product Hunt and Hacker News is positive, with developers praising the speed and simplicity of GPU deployment. Published case studies from Tavus, Creatium, DistilLabs, and bitHuman document strong customer satisfaction around cold-start performance, developer experience, and support responsiveness.
Pricing
Per-second, usage-based billing for all compute. GPU rates range from $0.000164/s (T4) to $0.00167/s (B200), with A10 at $0.000306/s and H100 at $0.000944/s. Memory is billed at $0.00000222/GB/s; CPU at $0.00000655/vCPU/s. Storage costs $0.05/GB/month (first 100 GB free). Three plan tiers: Hobby (free base + compute, up to 3 apps, 5 concurrent GPUs), Standard ($100/month + compute, unlimited apps, 30 concurrent GPUs, custom domains), and Enterprise (custom pricing, unlimited concurrency, dedicated Slack, volume discounts, ML engineering services). Volume discounts and capacity guarantees (e.g., up to 50 H100s with $10,000/month minimum spend) are available for enterprise deployments.
Limitations
- AWS and GCP cloud credits cannot be applied to Cerebrium usage, limiting its appeal for teams with existing hyperscaler commitments.
- The platform is optimized for bursty and variable workloads; always-on, high-utilization workloads may be more cost-effective on reserved instances.
- The G2 profile is unclaimed with zero published reviews, limiting third-party social proof.
- With approximately 13 employees as of early 2026, enterprise feature requests and dedicated SLA support may be constrained relative to larger vendors.
- Guaranteed capacity commitments require a minimum monthly spend (e.g., $10,000/month for H100 guarantees).
Frequently asked questions
Topic Coverage
Prompt-Level Results
| Prompt | Perplexity | ChatGPT | Gemini Search |
|---|---|---|---|
Capabilities0/5 cited (0%) | |||
Which GPU clouds support multi-modal model inference including vision, audio, and image generation? | |||
Which serverless AI providers offer EU data residency and sovereign infrastructure for regulated workloads? | |||
Which inference providers support custom model deployment beyond just popular open-source weights? | |||
What platforms offer fine-tuning APIs alongside inference for the same open-source models? | |||
What inference platforms provide LoRA adapter swapping at request time? | |||
Cost & Pricing0/5 cited (0%) | |||
Which inference platforms offer batch or async pricing tiers with significant discounts for non-realtime workloads? | |||
What serverless GPU platforms charge per-second so I'm not paying for idle time? | |||
Which GPU cloud providers offer spot or preemptible pricing for AI workloads? | |||
What's the most cost-effective way to run a high-volume RAG pipeline against an open-weights model? | |||
Which LLM inference providers offer the cheapest pricing per million tokens for open-source models? | |||
Performance1/5 cited (20%) | |||
What inference platforms deliver the highest tokens-per-second for Llama 70B and similar large models? | |||
Which LLM inference providers have the lowest cold start times for serverless GPU workloads? | |||
Which serverless AI platforms can handle bursty traffic to long-running model endpoints? | |||
Which GPU compute platforms scale to zero when idle and back up under load without minute-long delays? | |||
What are the best inference platforms for low-latency real-time agent workflows? | |||
Production Readiness1/5 cited (20%) | |||
Which LLM inference platforms have the most reliable uptime and SLAs for production workloads? | |||
What inference providers offer dedicated capacity or reserved GPU instances for predictable performance? | |||
Which GPU compute providers support running models inside a customer's VPC for compliance? | |||
What inference platforms include built-in observability, logging, and alerting for production model deployments? | |||
Which serverless GPU platforms have proven track records with high-traffic AI applications? | |||
Setup & First Run0/5 cited (0%) | |||
I need a hosted inference API for Llama or Mistral that I can hit with an OpenAI-compatible client — what are my options? | |||
What's the fastest way to deploy an open-source LLM behind an API endpoint without managing GPUs? | |||
Which inference platforms have the lowest learning curve for a frontend developer who just wants an API key? | |||
Which serverless GPU platforms let me run a Hugging Face model with a single CLI command? | |||
What's the easiest way to run my own fine-tuned model in production without provisioning GPUs? | |||
Strengths2
Which serverless GPU platforms have proven track records with high-traffic AI applications?
Avg # 2.0 · 1 platform
Which GPU compute platforms scale to zero when idle and back up under load without minute-long delays?
Avg # 3.0 · 1 platform
Gaps5
Which GPU clouds support multi-modal model inference including vision, audio, and image generation?
Competitors on 1 platform
What serverless GPU platforms charge per-second so I'm not paying for idle time?
Competitors on 1 platform
What inference providers offer dedicated capacity or reserved GPU instances for predictable performance?
Competitors on 1 platform
Which LLM inference providers have the lowest cold start times for serverless GPU workloads?
Competitors on 1 platform
What platforms offer fine-tuning APIs alongside inference for the same open-source models?
Competitors on 1 platform
Vertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | RunPod | 20.0% | 47.5% | 0.0% | 0.0% | 17.3% | #5.9 | +0.28 |
| 2 | Together AI | 6.7% | 17.5% | 0.0% | 1.3% | 6.7% | #5.0 | +0.33 |
| 3 | Beam | 4.0% | 15.0% | 0.0% | 0.0% | 4.0% | #5.3 | +0.08 |
| 4 | Modal Labs | 4.0% | 7.5% | 0.0% | 4.0% | 4.0% | #6.3 | +0.08 |
| 5 | Cerebrium | 2.7% | 7.5% | 0.0% | 0.0% | 1.3% | #4.3 | +0.25 |
| 6 | Baseten | 1.3% | 2.5% | 0.0% | 0.0% | 1.3% | #4.0 | +0.65 |
| 7 | Sference | 1.3% | 2.5% | 0.0% | 0.0% | 1.3% | #5.0 | +0.00 |
| 8 | Fireworks AI | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 9 | Lepton AI | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 10 | Replicate | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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