> This page is for Evo 2, version 2.2.0 (Latest) (default).
> For other versions, use one of these documentation indexes:
> - 2.2.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/evo2/2.2.0/llms.txt
> - 2.1.0: https://docs.nvidia.com/nim/bionemo/evo2/2.1.0/llms.txt
> - 2.0.0: https://docs.nvidia.com/nim/bionemo/evo2/2.0.0/llms.txt
> - 1.0.2: https://docs.nvidia.com/nim/bionemo/evo2/1.0.2/llms.txt
> - 1.0.1: https://docs.nvidia.com/nim/bionemo/evo2/1.0.1/llms.txt
> - 1.0.0: https://docs.nvidia.com/nim/bionemo/evo2/1.0.0/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nim/bionemo/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nim/bionemo/_mcp/server.

# Quickstart Guide for Evo 2 NIM

<Note>
Ensure you install and set up [Prerequisite Software](/nim/bionemo/evo2/prerequisites) (Docker, NGC CLI, NGC registry access) before you begin.
</Note>

## Start NIM

1. Export the `NGC_API_KEY` variable.

```bash
export NGC_API_KEY=<your personal NGC key>
```

2. The NIM container downloads models automatically. To save time and bandwidth,
   provide a local cache directory so the NIM can reuse models it has already
   downloaded. Run the following command to set up the cache directory.

```bash
export LOCAL_NIM_CACHE=~/.cache/nim
mkdir -p "$LOCAL_NIM_CACHE"
sudo chmod 0777 -R "$LOCAL_NIM_CACHE"
```

3. Run the NIM container with the following commands.

<Note>
To use the **7B model**, add `-e NIM_VARIANT=7b` to the docker run command below. By default, the NIM loads the 40B model.
</Note>

<Note>
You might need to adjust your GPU's indices.
</Note>

```bash
docker run -it \
    --runtime=nvidia \
    --gpus='"device=0,1"' \
    -p 8000:8000 \
    -e NGC_API_KEY \
    -v "$LOCAL_NIM_CACHE":/opt/nim/.cache \
    nvcr.io/nim/arc/evo2:2
```

This command starts the NIM container and exposes port 8000. The container defaults to the 40B model.

4. Open a new terminal, and leave the terminal with the service running. In the new terminal, wait until the health endpoint returns `{"status":"ready"}` before proceeding. This can take a couple of minutes. Query the health endpoint with the following command.

```bash
curl http://localhost:8000/v1/health/ready
```

## DNA Sequence Generation Examples

The following examples use the DNA Sequence Generation (Prediction) functionality to get started with the NIM.

Both Python and Shell examples provide input DNA sequence, number of generated nucleotides (`num_tokens`), as well as some optional parameters. The outputs of the examples will contain JSON objects with generated DNA nucleotides: adenine (A), thymine (T), guanine (G), and cytosine (C) in the `sequence` field, as well as other optional fields, such as sampled probabilities per nucleotide.

For descriptions of the APIs and parameters, refer to [Evo 2 NIM Endpoints](/nim/bionemo/evo2/endpoints). For information on assessing model accuracy, refer to [Benchmarking with Evo 2 NIM](/nim/bionemo/evo2/benchmarking).

### Python Client Example

The following is an example of how you can use a Python client to input a DNA sequence to generate its DNA nucleotides.

1. Save the following Python example to a file named `nim_client.py`.

```python
#!/usr/bin/env python3
import requests
import os
import json
from pathlib import Path

r = requests.post(
    url="http://localhost:8000/biology/arc/evo2/generate",
    json={
        "sequence": "ACTGACTGACTGACTG",
        "num_tokens": 8,
        "top_k": 1,
        "enable_sampled_probs": True,
    },
)

if "application/json" in r.headers.get("Content-Type", ""):
    print(r, "Saving to output.json:\n", r.text[:200], "...")
    Path("output.json").write_text(r.text)
elif "application/zip" in r.headers.get("Content-Type", ""):
    print(r, "Saving large response to data.zip")
    Path("data.zip").write_bytes(r.content)
else:
    print(r, r.headers, r.content)
```

2. Execute the example.

```bash
chmod +x nim_client.py

./nim_client.py
```

3. The example saves results to the `output.json` file in JSON format. You can view the file using the following command:

```bash
less output.json
```

### Shell Client Example

1. Save the following Shell example to a file named `nim_client.sh`.

```bash
#!/usr/bin/env bash
set -e

URL=http://localhost:8000/biology/arc/evo2/generate

request='{
 "sequence": "ACTGACTGACTGACTG",
 "num_tokens": 8,
 "top_k": 1,
 "enable_sampled_probs": true
}'
curl -H 'Content-Type: application/json' \
     -d "$request" "$URL"
```

2. Execute the example. The example displays the results to the terminal in JSON format.

```bash
chmod +x nim_client.sh

./nim_client.sh
```