Salad Cloud
Decentralized GPU cloud from $0.02/hr for AI inference and batch jobs.
If your AI workloads can tolerate spot-instance behavior and don't exceed 24GB VRAM (32GB on RTX 5090), SaladCloud is the cheapest GPU compute bar none — often 85%+ below hyperscalers. Skip it for anything latency-sensitive or needing strict SLAs.
- AI/ML inference at scale on a tight budget, especially image generation
- Batch processing and HPC workloads tolerant of interruption
- Startups and SMBs needing elastic GPU access without long-term commitments
- ZK proof generation and other compute-heavy decentralized workloads
- Real-time or latency-sensitive applications like live video processing
- Large model training requiring >24GB VRAM (32GB on RTX 5090 only)
- Production workloads that need strict SLAs or dedicated hardware
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Skip SaladCloud if you need guaranteed uptime, sub-second latency, or require GPU VRAM over 24 GB for training large models.
Going past 50 instances without a volume discount means paying full batch or on-demand rates, which can add up for large deployments — contact sales for custom pricing.
SaladCloud's batch pricing starting at $0.02/hr is dramatically cheaper than AWS (e.g., g4dn.xlarge ~$0.526/hr) or RunPod (~$0.114/hr for RTX 3090). Even on-demand prices (e.g., RTX 4090 at $0.204/hr) undercut most alternatives. Best for startups and cost-sensitive teams; enterprises needing SLAs should look at dedicated clouds.
In short
Salad Cloud — Decentralized GPU cloud from $0.02/hr for AI inference and batch jobs. Best for AI/ML inference at scale on a tight budget, especially image generation, Batch processing and HPC workloads tolerant of interruption, Startups and SMBs needing elastic GPU access without long-term commitments. Free to start; paid plans from $0.005/mo.
What's new in Salad Cloud
Checked 9 days agoAcross the latest 2 updates: 2 changelog entries.
Improved container download speed and networking reliability
Faster container downloads and more reliable networking for distributed workloads.
WSL2 compatibility improvements (v1.8.9)
Enhanced support for Windows Subsystem for Linux 2, improving developer experience on Windows.
Viability Score
How likely is Salad Cloud to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- 60,000+ daily active GPUs from $0.02/hr
- Salad Container Engine for managed container orchestration
- Global edge network spanning 191 countries
- On-demand elasticity with auto-scaling and no cold boot charges
- Automatic workload reallocation on node failure
- Container isolation and runtime host intrusion detection (Falco)
- Trust rating system for node performance and availability
- Pre-built model recipes for popular AI models
- Support for Nvidia RTX/GTX consumer GPUs (max 32GB VRAM on RTX 5090)
- Usage-based pricing with volume discounts for 50+ instances
- Virtual Kubelets for Kubernetes pod deployment
- Salad Gateway Service for dedicated proxies in ~200 countries
- Salad Transcription API for speech-to-text
- Improved container download speed and networking reliability (Sep 2025)
- WSL2 compatibility improvements (v1.8.9, Sep 2025)
About Salad Cloud
SaladCloud is a decentralized GPU cloud platform aggregating over 60,000 daily active consumer-grade Nvidia GPUs (RTX/GTX series) from a global network of individual providers. Designed for AI/ML inference, image generation, batch processing, and voice AI, it offers up to 90% cost savings versus traditional hyperscalers. Key features include the Salad Container Engine for managed orchestration, a global edge network spanning 191 countries, support for pre-built model recipes, and the newly released RTX 5090 instances at $0.294/hr (batch). The platform operates like spot instances but across a decentralized pool, with automatic failover and runtime security via host intrusion detection (Falco). Recent improvements (Sep 2025) boosted container download speeds and WSL2 compatibility, and the new RTX 5090 delivers 1.2s per image with Flux.1-Schnell. SaladCloud positions itself as a low-cost alternative to AWS, Azure, or GCP for workloads tolerant of longer cold starts and occasional interruptions, making it ideal for cost-sensitive teams and startups.
Behind the Verdict
SaladCloud fills a genuine gap: decentralized consumer GPUs at a fraction of hyperscaler prices. The platform is best for inference, image generation, ZK proofs, and batch jobs that can handle occasional interruptions. The new RTX 5090 at $0.294/hr with 32GB VRAM is a nice step up, but most GPUs cap at 24GB. Cold starts are longer than traditional cloud, and there are no compliance certifications. Compared to AWS spot instances, SaladCloud is much cheaper and easier to scale to hundreds of GPUs, but you get less reliability. We'd pick it for cost-constrained startups and research, but skip it for production services with uptime requirements.
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Real-world workflow fit
Concrete scenarios for the personas Salad Cloud actually fits — and what changes day-one when you adopt it.
Deploy a Stable Diffusion inference pipeline using the Salad Container Engine with pre-built model recipe.
Outcome: Serve 10 million images per day at 90% lower cost than AWS, with auto-scaling across hundreds of GPUs.
Submit batch jobs to 1,000+ consumer GPUs via Kubernetes using Virtual Kubelets.
Outcome: Complete simulations in days instead of weeks at a fraction of HPC cluster cost.
Use Salad Gateway Service to route requests through residential proxies in 200 countries.
Outcome: Collect diverse data without IP blocking, at lower cost than dedicated proxy services.
Use Cases
- Serve image generation inference at scale using consumer GPUs, reducing costs by up to 90%.
- Run zero-knowledge proof computations with 77% savings compared to datacenter alternatives.
- Power voice AI applications with up to 90% cost savings using distributed GPU nodes.
- Perform batch processing of massive jobs across thousands of low-cost GPUs.
- Collect data from thousands of residential IPs via Salad Gateway Service proxies.
- Scale molecular dynamics simulations on thousands of low-cost GPUs.
Limitations
- Consumer GPUs offer variable performance and availability; high-end datacenter GPUs are not available on demand.
- Best for workloads tolerant of interruptions or slower nodes.
- No free trial for container compute.
- Maximum GPU VRAM is 24 GB (RTX 4090).
- Cold start times longer than traditional clouds.
- Not suitable for latency-sensitive or mission-critical workloads.
as of 2026-06-28
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Salad Cloud tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Transcription API Free Trial
Free
GPU Instances (Batch)
$0.02/hr+
General Purpose Instances
$0.005/hr+
Volume Discount
Custom
Where the pricing makes sense
The company stage and team size where Salad Cloud's pricing actually pencils out — and where peers do it cheaper.
SaladCloud's batch pricing starting at $0.02/hr is dramatically cheaper than AWS (e.g., g4dn.xlarge ~$0.526/hr) or RunPod (~$0.114/hr for RTX 3090). Even on-demand prices (e.g., RTX 4090 at $0.204/hr) undercut most alternatives. Best for startups and cost-sensitive teams; enterprises needing SLAs should look at dedicated clouds.
Setup time & first value
How long it actually takes to get something useful out of Salad Cloud — broken out by persona, not the marketing-page minute.
For developers: deploying a container via Salad Container Engine or Virtual Kubelets takes about 1–2 hours including account creation, containerization, and configuration. First cold start may take 5–15 minutes due to node selection and download. Pre-built model recipes cut setup to under 30 minutes.
Switching to or from Salad Cloud
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From AWS/GCP/Azure: Containerize your workload with Docker, then deploy via Salad Container Engine or Virtual Kubelets. No code changes needed if you use standard container interfaces.
- ↗To AWS/GCP/Azure: Re-deploy your Docker containers on any Kubernetes cluster. Data migration requires manual transfer of model artifacts and storage.
Integrations
Resources & Guides
Official links
Tools that pair well with Salad Cloud
Common stack mates teams adopt alongside Salad Cloud, with the specific reason each pairing earns its keep.
Alternatives to Salad Cloud
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