app-store/apps/ollama-nvidia/metadata/description.md

## 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.