Ori Industries vs TensorDock
A detailed comparison to help you choose between Ori Industries and TensorDock.
Quick Verdict
3.5/5
Ori Industries
0 reviews
3.8/5
TensorDock
0 reviews
TensorDock is rated higher (3.8 vs 3.5). Ori Industries is a UK AI cloud company offering distributed GPU compute across their own and partner datacenters. Focused on UK and EU compliance for AI model training. TensorDock is a GPU compute marketplace with per-second billing — H100 SXM5 from $2.80/hour and A100 from $1.50/hour (A100 PCIe 80GB) on its published rate card. 100+ locations in 20+ countries, on-demand provisioning.
Ori Industries Distributed GPU infrastructure for ML training and inference | TensorDock Affordable GPU cloud compute without long-term contracts | |
|---|---|---|
| Overview | ||
| Rating | 3.5 (0 reviews) | 3.8 (0 reviews)✓ |
| Pricing model | paid | usage-based |
| Starting price | From $0.83/mo | From $0.1/mo✓ |
| Best for | ML teams and AI products that need current-generation NVIDIA GPUs at low cost with per-minute billing — especially UK/EU buyers wanting H200/H100 capacity on UK soil and organisations exploring a private AI cloud | Cost-conscious ML engineers, researchers and studios running training with checkpointing, batch inference or rendering, especially where consumer GPUs like the RTX 4090 fit the workload |
| Specifications (entry plan) | ||
| CPU cores | 8 vCPU✓ | 2 vCPU |
| RAM | 45 GB✓ | 4 GB |
| Storage | 300 GB✓ | 20 GB |
| Bandwidth | — | — |
| SLA uptime | — | 99.99% |
| Data-center count | 15 | 100✓ |
| €/vCPU/mo | €0.10 | €0.05✓ |
| €/GB RAM/mo | €0.02✓ | €0.03 |
| Features | ||
| IPv6 | ||
| DDoS protection | ||
| Automated backups | ||
| Snapshots | ||
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ||
| Free tier | ||
| Data-center locations | ||
| Regions | 15+ regions claimed (unlisted); UK region confirmed at Kao Data Harlow | 100+ marketplace locations in over 20 countries (US, EU, Asia-Pacific); tier 3/4 data centers plus community hosts |
| Tags | ||
| Tags | hourly billinggpu availableeu datacenter | hourly billinggpu availableeu datacenterus datacenter |
| Visit Ori Industries → | Visit TensorDock → | |
Ori Industries
Pros
- + Published, competitive GPU rates (H100 $2.90/h, H200 $3.50/h) with per-minute billing and no ingress or egress fees
- + Generous per-GPU host resources (24 vCPU / 240 GB RAM / 3 TB storage on single-H100 instances) and preinstalled ML stacks
- + Real UK data sovereignty option: first UK H200 deployment at Kao Data's Harlow campus (DGX-Ready, renewable-powered)
- + Single-GPU entry point (V100 $0.83/h) plus serverless Kubernetes, scale-to-zero inference, and 1,000+ GPU private clouds
Cons
- - No published uptime SLA and limited operational track record — contractual terms must be negotiated
- - Region list unpublished despite '15+ regions' claims; independent documentation and community coverage are thin
- - Young, venture-stage company mid-merger with Radiant — roadmap and pricing continuity carry counterparty risk
- - Compute-and-inference scope only: no managed database or full application platform; no free tier for evaluation
TensorDock
Pros
- + Among the lowest published GPU rates anywhere: RTX 4090 at $0.35/hr, H100 SXM5 at $2.85/hr typical
- + A la carte, per-second billing for vCPU, RAM and NVMe — pay only for the configuration you need
- + Breadth: 45 GPU models across 100+ locations in 20+ countries, with an API for automation
- + Published rate card and transparent explanation of why the same GPU has multiple prices
- + Host vetting, host SSH access revoked, and a 99.99% uptime standard for listed hosts
Cons
- - Marketplace variance: host redundancy and quality differ, with cheaper listings often least redundant
- - Email-only support with multi-hour response windows; no contractual SLA with credits
- - Prepaid balance model deletes servers when the balance reaches zero
- - Published rate card is stamped July 2024 and carries a no-guarantee disclaimer
- - Fewer managed niceties (templates, serverless) than RunPod, Lambda or hyperscalers
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