Quickstart

No prior GPU or AI experience needed. This guide gets you from zero to running AI in 5 minutes.

Step 1: Create Account & Add Funds

1. Go to clore.ai → Sign Up

2. Verify your email

3. Go to Account → Deposit

4. Add funds via CLORE, BTC, USDT, or USDC (minimum ~$5 to start)

Step 2: Pick a GPU

Go to the Marketplace and choose based on your task:

What I Want To Do	Minimum GPU	Budget/Day
Chat with AI (7B models)	RTX 3060 12GB	~$0.15
Chat with AI (32B models)	RTX 4090 24GB	~$0.50
Generate images (FLUX)	RTX 3090 24GB	~$0.30
Generate videos	RTX 4090 24GB	~$0.50
Generate music	Any GPU 4GB+	~$0.15
Voice cloning / TTS	RTX 3060 6GB+	~$0.15
Transcribe audio	RTX 3060 8GB+	~$0.15
Fine-tune a model	RTX 4090 24GB	~$0.50
Run 70B+ models	A100 80GB	~$2.00

Important — check more than just GPU!

• RAM: 16GB+ minimum for most AI workloads

• Network: 500Mbps+ recommended (models download from HuggingFace)

• Disk: 50GB+ free space for model storage

Quick GPU Guide

GPU	VRAM	Price	Sweet Spot For
RTX 3060	12GB	$0.15–0.30/day	TTS, music, small models
RTX 3090	24GB	$0.30–1.00/day	Image gen, 32B models
RTX 4090	24GB	$0.50–2.00/day	Everything up to 35B, fast inference
RTX 5090	32GB	$1.50–3.00/day	70B quantized, fastest
A100 80GB	80GB	$2.00–4.00/day	70B FP16, serious training
H100 80GB	80GB	$3.00–6.00/day	400B+ MoE models

Step 3: Deploy

Click Rent on your chosen server, then configure:

• Order type: On-Demand (guaranteed) or Spot (30–50% cheaper, can be interrupted)

• Docker image: See recipes below

• Ports: Always include 22/tcp (SSH) + your app port

• Environment: Add any API keys needed

🚀 One-Click Recipes

Chat with AI (Ollama + Open WebUI)

The easiest way to run local AI — ChatGPT-like interface with any open model.

Image: ghcr.io/open-webui/open-webui:ollama
Ports: 22/tcp, 8080/http

After deploy, open the HTTP URL → create account → pick a model (Llama 4 Scout, Gemma 3, Qwen3.5) → chat!

Image Generation (ComfyUI)

Node-based workflow for FLUX, Stable Diffusion, and more.

Image: yanwk/comfyui-boot:cu126-slim
Ports: 22/tcp, 8188/http
Environment: CLI_ARGS=--listen 0.0.0.0

Image Generation (Stable Diffusion WebUI)

Classic UI for Stable Diffusion, SDXL, and SD 3.5.

Image: universonic/stable-diffusion-webui:latest
Ports: 22/tcp, 8080/http

LLM API Server (vLLM)

Production-grade serving with OpenAI-compatible API.

Image: vllm/vllm-openai:latest
Ports: 22/tcp, 8000/http
Command: vllm serve Qwen/Qwen3.5-9B-Instruct --host 0.0.0.0 --max-model-len 8192

Music Generation (ACE-Step)

Generate full songs with vocals — works on any 4GB+ GPU!

Ports: 22/tcp, 7860/http

SSH in, then:

git clone https://github.com/ACE-Step/ACE-Step-1.5.git && cd ACE-Step-1.5
pip install -r requirements.txt
python app.py --port 7860 --listen 0.0.0.0

Step 4: Connect

After your order starts:

1. Go to My Orders → find your active order

2. Web UI: Click the HTTP URL (e.g., https://xxx.clorecloud.net)

3. SSH: ssh -p <port> root@<proxy-address>

First launch takes 5–20 minutes — the server downloads AI models from HuggingFace. HTTP 502 errors during this time are normal. Wait and refresh.

Deploy	Typical Startup
Ollama + Open WebUI	3–5 min
ComfyUI	10–15 min
vLLM	5–15 min (depends on model size)
SD WebUI	10–20 min

Step 5: Start Creating

Once your service is running, explore the guides for your specific use case:

🤖 Language Models (Chat, Code, Reasoning)

• Ollama — easiest model management

• Llama 4 Scout — Meta's latest, 10M context

• Gemma 3 — Google's 27B that beats 405B models

• Qwen3.5 — beat Claude 4.5 on math (Feb 2026!)

• DeepSeek-R1 — chain-of-thought reasoning

• vLLM — production API serving

🎨 Image Generation

• FLUX.2 Klein — < 0.5 sec per image!

• ComfyUI — node-based workflows

• FLUX.1 — highest quality with LoRA + ControlNet

• Stable Diffusion 3.5 — best text rendering

🎬 Video Generation

• FramePack — only 6GB VRAM needed!

• Wan2.1 — high quality T2V + I2V

• LTX-2 — video WITH audio

• CogVideoX — Zhipu AI's video model

🔊 Audio & Voice

• Qwen3-TTS — voice cloning, 10+ languages

• WhisperX — transcription + speaker diarization

• Dia TTS — multi-speaker dialog

• Kokoro — tiny TTS, only 2GB VRAM

🎵 Music

• ACE-Step — full songs on < 4GB VRAM

💻 AI Coding

• TabbyML — self-hosted Copilot for $4.50/month

• Aider — terminal AI coding assistant

🧠 Training

• Unsloth — 2x faster, 70% less VRAM

• Axolotl — YAML-based fine-tuning

💡 Tips for Beginners

1. Start with Ollama — it's the easiest way to try AI locally

2. RTX 4090 is the sweet spot — handles 90% of use cases at $0.50–2/day

3. Use Spot orders for experiments — 30–50% cheaper

4. Use On-Demand for important work — guaranteed, no interruptions

5. Download your outputs before the order ends — files are deleted after

6. Pay with CLORE token — often better rates than stablecoins

7. Check RAM and network — low RAM is the #1 cause of failures

Troubleshooting

Problem	Solution
HTTP 502 for a long time	Wait 10–20 min for first startup; check RAM ≥ 16GB
Service won't start	RAM too low (need 16GB+) or VRAM too small for the model
Slow model download	Normal on first run; prefer 500Mbps+ servers
CUDA out of memory	Use smaller model or bigger GPU; try quantized versions
Can't SSH	Check port is 22/tcp in config; wait for server to fully start

🐍 Python SDK & CLI (Recommended)

Prefer code over clicking? Install the official SDK:

pip install clore-ai
clore search --gpu "RTX 4090" --max-price 5.0
clore deploy 123 --image cloreai/ubuntu22.04-cuda12 --type on-demand --currency bitcoin --ssh-password mypass --port 22:tcp
clore ssh 456

Or use Python directly:

from clore_ai import CloreAI

client = CloreAI()
servers = client.marketplace(gpu="RTX 4090", max_price_usd=5.0)
order = client.create_order(server_id=servers[0].id, image="cloreai/ubuntu22.04-cuda12", type="on-demand", currency="bitcoin")

→ Full Python Quickstart | SDK Guide | CLI Automation

Need Help?

• 📖 Full Troubleshooting Guide

• 📊 GPU Comparison Chart

• 💰 Pricing Reference

• 💬 Discord

• 💬 Telegram

• 📧 [e-mail]