Modal: Delivers effortless Python serverless execution for AI pipelines, but focuses on function-as-a-service rather than raw VMs. Modal records 1,196,021 monthly visits with +30.2% month-over-month growth and Freemium, Contact for Pricing pricing. Salad records 713,519 monthly visits with +10.4% growth and Free Trial, Paid, Contact for Pricing pricing.
Serverless cloud infrastructure for AI and data workloads
Distributed GPU cloud that orchestrates the world's idle consumer GPUs
| Dimension / Metric | | |
|---|---|---|
| Official Domain | modal.com | salad.com |
| Pricing Model | Freemium, Contact for Pricing | Free Trial, Paid, Contact for Pricing |
| Monthly Visits | 1.2M (1,196,021) | 713.52K (713,519) |
| MoM Traffic Delta | +277.18K (+30.2%) | +67.49K (+10.4%) |
| Primary Market & Share | 🇺🇸 United States (43.9%) | 🇺🇸 United States (40.9%) |
| Direct Visits / mo | 845.64K | 440.92K |
| User Rating | 4.8 | 4.3 |
| Supported Platforms | Website | Website |
Serverless cloud infrastructure for AI and data workloads
Write plain Python, attach GPUs or containers, and deploy HTTPS endpoints that autoscale with traffic and scale to zero when idle.
Launch isolated, secure environments for coding agents, RL rollouts, and untrusted code, with sub-second starts and support for over a million concurrent sandboxes.
Run fine-tunes, LoRA, full training, and reinforcement learning on elastic single or multi-node GPU capacity with no quota requests.
Serve LLMs and image, video, or audio models through OpenAI-compatible endpoints, or bring your own inference stack and let Modal handle the infrastructure.
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.
SpecialistExtremely fast serverless execution optimized specifically for generative media models rather than general Python code.
SpecialistExtremely fast serverless execution optimized specifically for generative media models rather than general Python code.
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.
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.
Easier model packaging via Cog, but offers less arbitrary serverless Python container execution than Modal.
Easier model packaging via Cog, but offers less arbitrary serverless Python container execution than Modal.
SpecialistOffers extremely cheap serverless model hosting via API, but does not provide raw containerized GPU instances.
Provides integrated development studios and training workflows, but with less granular serverless function orchestration.
Provides integrated development studios and training workflows, but with less granular serverless function orchestration.
SpecialistCombines ready-to-use model APIs and serverless GPU jobs, with simpler API consumption than custom Modal apps.
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.
