Rent an RTX 4070 Ti for the AI hobbyist sweet spot. 12 GB GDDR6X with 7,680 Ada cores — Flux production batches at ~1.1 s per image, 7B QLoRA fine-tunes finishing in under six hours, Llama-3 13B INT8 served via vLLM. Spun up in under 90 seconds, billed per-minute, paid in BTC, USDT/USDC or CLORE. The card that turns a weekend into a finished fine-tune.
4070 Ti is the prosumer's Ada card — 12 GB VRAM, 7,680 cores, full bandwidth for Flux production. Great for SDXL pipelines, 7B QLoRA, and 13B INT8 serving without the 4080's price.
Sits between the 4070 and 4080 on every benchmark while staying friendlier on price. 12 GB Ada handles Flux Schnell at ~1.1 s/image, 7B QLoRA finishes in under 6 hours, 13B INT8 serves via vLLM. The card hobbyists pick when they're starting to ship real fine-tunes.
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.
When you want better-than-4070 throughput but the 4080 is overkill. The 4070 Ti's 7,680 Ada cores nail the price/performance sweet spot. 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 4070 Ti, 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.
Often yes — it sits right between the 4070 and 4080 in throughput at a friendlier price. 12 GB Ada VRAM runs Flux/SDXL production, 7B QLoRA, and 13B INT8 inference. If you need 16 GB go 4080; if budget-tight stick with 4070.
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.
12 GB Ada with 7,680 cores — the sweet spot for hobbyist Flux production and 13B INT8 serving.
Schnell variant is purpose-built for 4-step generation — ideal for batch image pipelines on a 12 GB card.
Read the guide →Mistral/Llama 7B QLoRA at 4K context; 4070 Ti finishes a 50K-sample run in under 6 hours.
Read the guide →SVD with offload fits in 12 GB; longer 25-frame variants want a 4080 with 16 GB.
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.
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