Rent an RTX 3070 for the price of a coffee per hour. 8 GB GDDR6 is the right floor for first-time AI dev boxes — Stable Diffusion 1.5, SDXL at 768², Llama-3 8B INT4 chat, Whisper transcription, YOLOv8 inference. Spun up in under 90 seconds, billed per-minute, paid in BTC, USDT/USDC or CLORE. Cheaper than a Colab Pro subscription and the GPU is yours for the whole minute.
Three years in, the 3070 is still one of the most rented cards on the network. NVLink-capable, 8 GB, and cheap — ideal for hobbyists, students, and side projects.
The cheapest entry to the AI dev box. Quantized 8B LLMs, SD 1.5 production, and YOLO inference run comfortably — and a full hour of compute costs less than a takeaway coffee. Perfect first card for hobbyists, students, and anyone benchmarking before scaling up.
SD 1.5, SDXL, ComfyUI workflows. Blender Cycles with OptiX delivers solid 1080p–4K renders at hobbyist-friendly cost.
vLLM and TGI containers run 7B–13B FP16 models with comfortable batch sizes. The cheapest path to production-grade open-source inference.
Older silicon, but 8 GB is 8 GB. For workloads that fit, the 3070 is the cheapest path to a real GPU. Specs from Nvidia's reference sheet.
// prices are spot-market lows · refreshed every 60 s
Every server is priced by its host. These are the live floors across the marketplace — you'll see hundreds of variants once you're in.
No sales call. No quota request. No three-week procurement. The first four commands are all you need.
Filter the marketplace by RTX 3070, country, GPU count, reliability score, network speed.
Choose a Docker image — PyTorch, vLLM, ComfyUI, Blender — or paste your own.
You get a public endpoint, an SSH key, and Jupyter on port 8888 in under 90 s.
Per-minute billing rounds to the second. Stop the instance and the meter stops with it.
Yes — SDXL runs at 768² with optimizations like xformers, fp16, and tiled VAE. For full 1024² batch-2 you'll want a 3080 or 3090. Quantized 8B LLMs and SD 1.5 fit comfortably.
Consumer cards on CLORE.AI cover most hobby and indie workflows: Stable Diffusion 1.5 and SDXL, ComfyUI/Automatic1111, Flux.1, LoRA and QLoRA fine-tuning of 7B-13B LLMs, Whisper transcription, video transcoding, Blender Cycles, and game-server hosting. Anything that fits in 8-32 GB VRAM and runs in Docker runs here. You get full root SSH plus a Jupyter template if you want one.
Cold-start lands in roughly 60-90 seconds for a typical Docker image: server allocation, container pull, GPU passthrough, SSH up. Pre-cached templates (PyTorch, ComfyUI, vLLM, Ollama) are faster because the image is already on the host. Once running you pay per minute, so a 10-minute experiment costs ten minutes of rental, not an hour.
On-demand is a fixed per-hour price the host sets; the rental cannot be revoked while you have funds. Spot is auction-style: you bid, the highest bidder runs, and a higher bidder can preempt you. Spot is typically 30-50% cheaper. CLORE.AI charges 2.5% on spot and 10% on on-demand, split 50/50 with the host.
Spot prices on CLORE.AI usually beat RunPod community pricing because there is no centralized markup; you rent directly from the host with a 2.5% spot fee. Vast.ai is the closest comparison, and on consumer cards CLORE.AI is generally within a few cents per hour. Hold CLORE in your wallet for Proof of Holding and you stack up to 50% off the marketplace fee.
Yes. Point at any registry - Docker Hub, GHCR, Quay, your private registry - then set env vars, port forwards, and your SSH public key in the rent dialog. Templates on the platform are just preset configs; nothing is locked down. You get full root inside the container with GPU passthrough.
An 8 GB Ampere card that punches above its weight on quantized LLMs, SD 1.5 production, and lightweight inference pipelines.
8 GB VRAM is tight for SDXL — stick to 768² with tiled VAE, or fall back to SD 1.5 for batch 4 at 512².
Read the guide →Quantized 8B weights consume ~5 GB VRAM — leaves headroom for 8K-context chats and a small embedding model.
Read the guide →Streaming transcription jobs cost a few cents per hour of audio at 3070 spot prices.
Read the guide →Side-by-side specs across the consumer tier. Click any row to see that GPU.
Step-by-step guides verified on CLORE.AI hardware. Pick a workload, copy the docker image, ship in minutes.
Per-minute payouts in BTC, USDT, USDC or CLORE. No listing fee, no contracts, withdraw any time.
Hosts around the world are accepting workloads right now. Sign up, top up your wallet, and the next hour is yours.