Meta’s Llama models are some of the most widely used open-weight AI models. Llama 3.1 and 3.3 (8B, 70B and 405B) and the Llama 4 Mixture-of-Experts models (Scout and Maverick) power thousands of self-hosted chatbots, coding assistants and AI agents. Here is how much GPU you need and where to host them.
🧮 Not sure which GPU you need? Try our AI Model GPU Calculator: pick Llama, your context length and usage, and see the VRAM needed, the cheapest hosting and the API cost side by side.
Table of Contents
Which Llama Model Can You Run? (VRAM Requirements)
| Llama Model | Parameters | VRAM (4-bit) | VRAM (FP8/8-bit) | Recommended GPU |
|---|---|---|---|---|
| Llama 3.2 1B / 3B | 1–3B | 1–2 GB | 2–4 GB | Any 8 GB GPU |
| Llama 3.1 8B | 8B | ~5 GB | ~9 GB | RTX 4060, RTX A4000 |
| Llama 3.3 70B | 70B | ~42 GB | ~72 GB | RTX A6000 / A40 (4-bit), A100 80GB / H100 (8-bit) |
| Llama 4 Scout | 109B total, 17B active (MoE) | ~60 GB | ~110 GB | 1× H100 (4-bit), 2× H100 (FP8) |
| Llama 4 Maverick | 400B total, 17B active (MoE) | ~220 GB | ~400 GB | 4× H100/H200 (4-bit), 8× H100 (FP8) |
| Llama 3.1 405B | 405B dense | ~230 GB | ~410 GB | 8× H100 or H200 |
Figures are for model weights only; add 10–30% for the KV cache and context. Also compare Llama with newer open AI models like Qwen, Gemma 4, DeepSeek and Mistral, which often beat it at the same size.
Best Llama Hosting Providers
1. GPU Mart
- Dedicated GPU servers and GPU VPS (US)
- GPUs from P1000 to RTX 5090, RTX PRO 6000, A100 and H100
- One-click AI apps: Ollama, Stable Diffusion, ComfyUI
- GPU VPS from $21/mo · RTX 4090 $409/mo · RTX 5090 from $419/mo · A100 80GB $1,559/mo · H100 $2,099/mo
Pros
- Lowest monthly prices for dedicated GPUs
- Full root/admin access, Windows or Linux
- Multi-GPU servers available
Cons
- Monthly billing only
- US data centers only
RTX 4090 ($409/month) for Llama 3.1 8B at full speed; RTX A6000 ($409/month) or 4× A6000 ($1,199/month) for Llama 3.3 70B; one-click Ollama included.
2. HOSTKEY
- GPU servers in the EU, UK and US
- RTX 4090, RTX 5090, RTX PRO 6000, A100, H100
- Pre-installed AI stack: Ollama, Open WebUI, ComfyUI
- GTX 1080 Ti from €70/mo · RTX 4090 €279/mo · RTX 5090 €590/mo · A100 80GB €1,300/mo · H100 €1,590/mo
Pros
- Hourly or monthly billing
- GDPR-friendly EU hosting
- Big-VRAM options
Cons
- Popular GPUs sell out
- Setup slower than cloud pods
Servers with Ollama + Open WebUI pre-installed; RTX PRO 6000 (96 GB) fits Llama 4 Scout in 4-bit on one GPU.
3. RunPod
- Per-second billing in 30+ regions
- Templates: vLLM, ComfyUI, PyTorch, Ollama, Jupyter
- Serverless AI endpoints
- RTX 3090 $0.22/hr · RTX 4090 $0.34/hr · A100 $1.19/hr · H100 $1.99/hr · H200 $3.59/hr (Community Cloud)
Pros
- Very cheap consumer GPUs
- Huge GPU choice up to B200
- Fast start-up
Cons
- Storage billed when stopped
- Community hosts vary
vLLM templates; A6000 $0.33/hour for 70B in 4-bit, H100 from $1.99/hour for Llama 4 Scout.
4. Lambda
- On-demand GPU cloud built for AI
- Lambda Stack pre-installed
- 1× to 8× GPU instances and clusters
- A6000 $1.09/hr · A100 40GB $1.99/hr · GH200 $2.29/hr · H100 SXM from $3.99/hr · B200 from $6.69/hr
Pros
- Reliable data-center GPUs
- No egress fees
- Simple pricing
Cons
- GPUs can sell out
- No monthly servers
8× H100 SXM nodes (from $3.99/GPU-hour) handle Llama 4 Maverick and Llama 3.1 405B.
How to Run Llama on a GPU Server
# Easiest: Ollama
curl -fsSL https://ollama.com/install.sh | sh
ollama run llama3.1:8b
# Production: vLLM (OpenAI-compatible API)
pip install vllm
vllm serve meta-llama/Llama-3.3-70B-Instruct --tensor-parallel-size 2Llama weights on Hugging Face require accepting Meta’s licence first. The Llama Community License allows commercial use, with extra terms for very large companies.
FAQ
Any GPU with 8 GB+ VRAM in 4-bit; 16–24 GB for full precision and long context.
Yes, in 4-bit on a 48 GB GPU (RTX A6000, A40, L40S) or in 8-bit on an 80 GB A100/H100.
Yes, under the Llama Community License, with extra conditions for companies with very large user bases.
Conclusion
For Llama 8B and 70B, a monthly RTX 4090 or RTX A6000 from GPU Mart or HOSTKEY is the best value; for Llama 4 and 405B, use multi-GPU H100 nodes on Lambda or RunPod.
Prices were checked in September 2026 and change often. Always confirm current pricing on the provider’s website before you order.