## Nvidia Instructions
To enable your Nvidia GPU in Docker:
- You need to install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installation)
- And configure Docker to use Nvidia driver
```sh
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker
```
---
## Usage
⚠️ This app runs on port **11435**. Take this into account when configuring tools connecting to the app.
### Use with a frontend
- [LobeChat](https://github.com/lobehub/lobe-chat)
- [LibreChat](https://github.com/danny-avila/LibreChat)
- [OpenWebUI](https://github.com/open-webui/open-webui)
- [And more ...](https://github.com/ollama/ollama)
---
### Try the REST API
Ollama has a REST API for running and managing models.
**Generate a response**
```sh
curl http://localhost:11434/api/generate -d '{
"model": "llama3",
"prompt":"Why is the sky blue?"
}'
```
**Chat with a model**
```sh
curl http://localhost:11434/api/chat -d '{
"model": "llama3",
"messages": [
{ "role": "user", "content": "why is the sky blue?" }
]
}'
```
---
## Compatible GPUs
Ollama supports Nvidia GPUs with compute capability 5.0+.
Check your compute compatibility to see if your card is supported:
[https://developer.nvidia.com/cuda-gpus](https://developer.nvidia.com/cuda-gpus)
| Compute Capability | Family | Cards |
| ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
| 9.0 | NVIDIA | `H100` |
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080` `RTX 4070 Ti` `RTX 4060 Ti` |
| | NVIDIA Professional | `L4` `L40` `RTX 6000` |
| 8.6 | GeForce RTX 30xx | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060` |
| | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2` |
| 8.0 | NVIDIA | `A100` `A30` |
| 7.5 | GeForce GTX/RTX | `GTX 1650 Ti` `TITAN RTX` `RTX 2080 Ti` `RTX 2080` `RTX 2070` `RTX 2060` |
| | NVIDIA Professional | `T4` `RTX 5000` `RTX 4000` `RTX 3000` `T2000` `T1200` `T1000` `T600` `T500` |
| | Quadro | `RTX 8000` `RTX 6000` `RTX 5000` `RTX 4000` |
| 7.0 | NVIDIA | `TITAN V` `V100` `Quadro GV100` |
| 6.1 | NVIDIA TITAN | `TITAN Xp` `TITAN X` |
| | GeForce GTX | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050` |
| | Quadro | `P6000` `P5200` `P4200` `P3200` `P5000` `P4000` `P3000` `P2200` `P2000` `P1000` `P620` `P600` `P500` `P520` |
| | Tesla | `P40` `P4` |
| 6.0 | NVIDIA | `Tesla P100` `Quadro GP100` |
| 5.2 | GeForce GTX | `GTX TITAN X` `GTX 980 Ti` `GTX 980` `GTX 970` `GTX 960` `GTX 950` |
| | Quadro | `M6000 24GB` `M6000` `M5000` `M5500M` `M4000` `M2200` `M2000` `M620` |
| | Tesla | `M60` `M40` |
| 5.0 | GeForce GTX | `GTX 750 Ti` `GTX 750` `NVS 810` |
| | Quadro | `K2200` `K1200` `K620` `M1200` `M520` `M5000M` `M4000M` `M3000M` `M2000M` `M1000M` `K620M` `M600M` `M500M` |
---
## Model library
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
Here are some example models that can be downloaded:
| Model | Parameters | Size | Download |
| ------------------ | ---------- | ----- | ------------------------------ |
| Llama 3 | 8B | 4.7GB | `ollama run llama3` |
| Llama 3 | 70B | 40GB | `ollama run llama3:70b` |
| Phi-3 | 3,8B | 2.3GB | `ollama run phi3` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
| Starling | 7B | 4.1GB | `ollama run starling-lm` |
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Gemma | 2B | 1.4GB | `ollama run gemma:2b` |
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
| Solar | 10.7B | 6.1GB | `ollama run solar` |
> Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.