Cerebrium: Optimizes fast cold starts for real-time model inference, but lacks generalized container orchestration features. Cerebrium records 26,974 monthly visits with -50.8% month-over-month growth and Free Trial, Paid pricing. Salad records 713,519 monthly visits with +10.4% growth and Free Trial, Paid, Contact for Pricing pricing.
Serverless GPUs for real-time AI with sub-second cold starts
Distributed GPU cloud that orchestrates the world's idle consumer GPUs
| Dimension / Metric | | |
|---|---|---|
| Official Domain | cerebrium.ai | salad.com |
| Pricing Model | Free Trial, Paid | Free Trial, Paid, Contact for Pricing |
| Monthly Visits | 26.97K (26,974) | 713.52K (713,519) |
| MoM Traffic Delta | -27.82K (-50.8%) | +67.49K (+10.4%) |
| Primary Market & Share | 🇺🇸 United States (22.3%) | 🇺🇸 United States (40.9%) |
| Direct Visits / mo | 15.05K | 440.92K |
| User Rating | 4.3 | 4.3 |
| Supported Platforms | Website | Website |
Serverless GPUs for real-time AI with sub-second cold starts
Memory and GPU snapshotting restores containers in roughly 2–4 seconds, which is essential for voice agents and other interactive workloads.
Access thousands of GPUs across 12+ GPU types and multiple clouds with no reservations or lock-in, scaling automatically on traffic bursts.
Deploy LLMs, voice pipelines, and image or video models from your own code or Dockerfile, with REST, WebSocket, and streaming endpoints.
Real-time logs, metrics, and scaling events with native OpenTelemetry support for plugging into existing monitoring tools.
Distributed GPU cloud that orchestrates the world's idle consumer GPUs
Schedules, monitors and reallocates Docker/OCI workloads across thousands of distributed GPU nodes, with failover when nodes disappear.
On-demand access to a distributed pool of idle consumer GPUs across 190+ countries with priority pricing from about $0.015 per GPU-hour.
A managed token endpoint for open-weight models priced per token, with your data never used for training.
Run the same orchestration stack inside your organisation, pooling idle workstation GPUs into an internal OpenAI-compatible service.
Offers reliable dedicated and serverless GPU rentals, but lacks Salad's ultra-low-cost peer-to-peer consumer hardware pool.
Offers reliable dedicated and serverless GPU rentals, but lacks Salad's ultra-low-cost peer-to-peer consumer hardware pool.
SpecialistSpecializes in managed serverless inference APIs for open-source models, rather than raw GPU infrastructure rentals.
SpecialistSpecializes in managed serverless inference APIs for open-source models, rather than raw GPU infrastructure rentals.
Provides an extensive peer-to-peer GPU marketplace with lower prices, but requires more manual configuration.
Provides an extensive peer-to-peer GPU marketplace with lower prices, but requires more manual configuration.
SpecialistDelivers effortless Python serverless execution for AI pipelines, but focuses on function-as-a-service rather than raw VMs.
SpecialistDelivers effortless Python serverless execution for AI pipelines, but focuses on function-as-a-service rather than raw VMs.
Supplies enterprise-grade NVIDIA GPU clusters and managed ML tooling, but at a higher professional price point.
Supplies enterprise-grade NVIDIA GPU clusters and managed ML tooling, but at a higher professional price point.
SpecialistOffers extremely cheap serverless model hosting via API, but does not provide raw containerized GPU instances.
The AI cloud built by the creators of PyTorch Lightning
One cloud for 200+ model APIs, agent sandboxes and GPU compute
Focuses on large-scale enterprise GPU clusters for training, rather than lightweight consumer container workloads.
Focuses on large-scale enterprise GPU clusters for training, rather than lightweight consumer container workloads.
Features second-billed persistent SSH GPU instances, but lacks a distributed consumer hardware backbone.
Features second-billed persistent SSH GPU instances, but lacks a distributed consumer hardware backbone.
SpecialistScales distributed Ray workloads effortlessly across clusters, but is tailored for heavy data engineering and training.
SpecialistScales distributed Ray workloads effortlessly across clusters, but is tailored for heavy data engineering and training.
Gives access to competitive cloud GPU virtual machines, but operates traditional data centers instead of P2P.
Gives access to competitive cloud GPU virtual machines, but operates traditional data centers instead of P2P.
