TensorDock vs LowCostGPU at a glance
TensorDock
GPU marketplace: independent hosts set prices across 100+ locations
LowCostGPU
Fixed prices at market median × 0.70, crypto only, verified datacenters
| TensorDock | LowCostGPU | |
|---|---|---|
| Billing | Per second (GPU + vCPU + RAM + storage billed separately) | Per second, no minimum, price locked at deploy |
| Payment | Card, prepaid balance | Crypto only — USDT (TRC-20/ERC-20), BTC, XMR, LTC, ETH, TRX, SOL |
| Identity | Email and card | Email + password. No KYC, no card, no stored IP addresses |
| Free credit | None | None — every hour is ≥30% under the market median instead |
| Cheaper tier | Spot on some hosts | Interruptible flat −50% (no auction) · reserved −35% (3+ months) |
| Regions | 100+ locations (independent hosts) | 32 regions on 5 continents, verified datacenters only |
| Minimums | None | None — 1× to 8× GPUs at the same per-GPU price |
| Storage | NVMe ~$0.036/GB/mo + $0.003/vCPU-hr + $0.002/GB RAM-hr | $0.08/GB/month NVMe, volumes survive instances |
| Egress | Not itemised | $0.01/GB in and out, every region |
| Access | VMs and containers, SSH, API | Containers or full KVM VMs, SSH, Jupyter, REST API, CLI, Python SDK |
TensorDock column: as published on tensordock.com on 2026-09-03. Details change — verify before you decide.
TensorDock vs LowCostGPU prices, GPU by GPU
Public on-demand list prices per GPU-hour on TensorDock's pricing page (2026-09-03) against LowCostGPU's fixed rates today — every LowCostGPU price is the public marketplace median × 0.70, rounded down, re-checked weekly.
| GPU | TensorDock list | LowCostGPU on-demand | LowCostGPU interruptible | Difference |
|---|---|---|---|---|
| H100 SXM from; hosts set prices | $2.25 | $1.680 | $0.840 | −25% on LowCostGPU |
| A100 SXM4 from | $1.80 | $0.468 | $0.234 | −74% on LowCostGPU |
| A100 PCIE from | $1.50 | $0.388 | $0.194 | −74% on LowCostGPU |
| L40 from | $0.95 | $0.318 | $0.159 | −67% on LowCostGPU |
| RTX 6000Ada from | $0.75 | $0.495 | $0.247 | −34% on LowCostGPU |
| RTX A6000 from | $0.45 | $0.281 | $0.140 | −38% on LowCostGPU |
| RTX 4090 from | $0.35 | $0.354 | $0.177 | +1% on LowCostGPU |
| RTX 3090 from | $0.20 | $0.148 | $0.074 | −26% on LowCostGPU |
| RTX A4000 from | $0.10 | $0.093 | $0.046 | −7% on LowCostGPU |
| Tesla V100 from | $0.17 | $0.093 | $0.046 | −45% on LowCostGPU |
Configurations differ (node sizes, tiers, regions); the note beside each card says which TensorDock price is quoted. Negative differences mean TensorDock is cheaper on that card.
When to stay with TensorDock
- You need a machine in one very specific city and a host happens to be there.
- You want the absolute floor price on an old card (A4000, V100) and accept host-dependent reliability.
- You are already comfortable with marketplace-style variance in hardware and uptime.
Why teams switch to LowCostGPU
- Fixed, all-inclusive prices: no separate vCPU, RAM or disk lines — the per-GPU rate includes the machine.
- Verified datacenters only, with a 99.9% SLA, instead of host-by-host reliability.
- Crypto payments with no card or KYC, and a flat −50% interruptible tier rather than per-host spot.
- Datacenter flagships (H100, H200, B200) always in stock at market median × 0.70, plus RTX 5090s.
Switching from TensorDock: what maps to what
| On TensorDock | On LowCostGPU |
|---|---|
| Host machine (VM) | Instance on a verified datacenter machine — same CPU/RAM class shown on every offer |
| Spot host | Interruptible instance, flat −50% |
| Separate vCPU / RAM / NVMe lines | Included in the per-GPU price; storage $0.08/GB/month |
| TensorDock API | REST API, CLI, Python SDK |
pip install lowcostgpu
export LOWCOSTGPU_API_KEY=pg_live_… # console → API keys
lowcostgpu launch --gpu h100-sxm --template pytorch --disk 100 --volume data:/data
# ✓ instance i-52ab77c1 running (24.1s) · $1.680/hr · per second
lowcostgpu stop i-52ab77c1 # billing ends this secondData moves the boring way: rsync or rclone from your TensorDock machine to a LowCostGPU volume, which then mounts on every future instance in seconds. Templates for PyTorch, vLLM, ComfyUI and Ollama are official images; anything else runs from its OCI reference.
A real month, costed
| Scenario | TensorDock | LowCostGPU |
|---|---|---|
| 1× H100 SXM, 730 hours on-demand | $1,643 | $1,226 |
| 1× H100 SXM, 8 h/day × 20 days | $360 | $269 |
| Same 160 hours, LowCostGPU interruptible | — | $134 |
| 500 GB of storage, one month | NVMe ~$0.036/GB/mo + $0.003/vCPU-hr + $0.002/GB RAM-hr | $40 |
Run your own schedule through the cost calculator — it adds storage and bandwidth and compares against the marketplace median.
TensorDock alternative: FAQ
Is LowCostGPU cheaper than TensorDock?
On flagships, yes: TensorDock hosts list the H100 SXM from $2.25/hr and the A100 SXM from $1.80/hr before vCPU, RAM and disk (checked 2026-09-03); LowCostGPU fixes both at market median × 0.70 all-inclusive. On the cheapest legacy cards TensorDock hosts can be a few cents lower per hour.
Are LowCostGPU machines from independent hosts?
No. Every machine sits in a Tier-III colocation facility with redundant power and network, burned in for 72 hours before it is listed. There are no residential hosts.
Do you charge separately for CPU and RAM?
No — the per-GPU price includes the vCPUs and RAM shown on the offer. Only storage and bandwidth are separate lines.
Try the switch for the price of a coffee
Top up $40 in USDT or Monero, deploy the same image you run on TensorDock, and benchmark it. No card, no KYC, per-second billing — stop it the minute you are done.
TensorDock and its logo are trademarks of their owner, used here only to identify the compared service; LowCostGPU is not affiliated with TensorDock. NVIDIA GPU names are trademarks of NVIDIA Corporation.
