# Testnet (Closed)

{% hint style="danger" %}
**Importance**: 

The Pictor Network Testnet on Aptos has officially closed. We appreciate everyone’s participation. 
{% endhint %}

## Campaign Overview

{% hint style="info" %}
**Important Information**:

1. 🌐**Testnet page**: [https://testnet.pictor.network/](https://testnet.pictor.network/login/)
2. 📅 **Campaign Period**: July 25 – August 23, 2025 (UTC).
3. **🏆 Leaderboard & Rewards**: The **top 100 users** will split a Reward Pool of **$2,000 worth of APT**, based on final **point ranking** at the end of the campaign. 
4. **🧩 Roles**: Join as a **Creator**, **Worker**, or **Community Member** — or take on **multiple roles** to earn more points and climb the leaderboard faster.
   {% endhint %}

## How to Participate

### General Guide

Getting started is easy. All roles follow the same steps as follows:

**Step 1: Sign Up**:\
Visit the [Pictor Testnet page](https://testnet.pictor.network/), and choose one of the following methods:

* **Sign in with Google:**\
  A keyless Aptos account is automatically created for you within Aptos Connect.
* **Connect Aptos Wallet:**\
  Use your Aptos wallet (e.g., Petra) to sign in directly.

{% hint style="warning" %}
**Important Notes**: 

1. The Keyless Aptos account created via Aptos Connect is directly linked to the Google account you use to sign in. If you lose access to your Google account, you will also lose access to the associated Aptos blockchain account.
2. 🔐 To keep your account secure, we strongly recommend **enabling two-factor authentication** (2FA) on your Google account.
   {% endhint %}

**Step 2: Choose a Role**\
Select whether you want to join as a **Creator, Worker, or Community Member**.

* **Creator**: Go to the **Rendering** section, submit Blender rendering jobs for Workers in the network to process.
* **Worker**: Go to the **My Workers** section, download and install the Pictor Worker app, create a new Worker, connect your device, and start contributing your GPU power to the network.
* **Community Member**: Go to the **Rewards** section, complete the listed tasks.

**Step 3: Start Earning Points**\
Complete tasks based on your role:

* **Creator**: Claim credits to submit jobs and earn points for every job rendered successfully.
* **Worker**: Earn points based on the tasks you have rendered and your Worker Nodes' total online time.
* **Community Member**: Earn points by checking in daily, completing social tasks, and inviting friends to join the campaign.

**Step 4: Track Your Point Earnings**

View the total points you have earned directly in your dashboard.

**Step 5: Climb the Leaderboard**\
Visit the global [Leaderboard](https://testnet.pictor.network/leaderboard) to see your ranking among all testnet participants.

The **top 100 users** will split a reward pool of **$2,000 worth of APT (Aptos token)** based on their final **point** ranks, so every point counts.

Here’s how the rewards are distributed:

<table><thead><tr><th width="139.72723388671875">🏆 Rank</th><th width="250.0909423828125" align="center">💰 Total Reward (in APT)</th><th width="250" align="center">💸 Reward per User (in APT)</th></tr></thead><tbody><tr><td>#1</td><td align="center">$200</td><td align="center">$200</td></tr><tr><td>#2–5</td><td align="center">$400</td><td align="center">$100</td></tr><tr><td>#6–15</td><td align="center">$500</td><td align="center">$50</td></tr><tr><td>#16–50</td><td align="center">$500</td><td align="center">$14</td></tr><tr><td>#51–100</td><td align="center">$400</td><td align="center">$8</td></tr></tbody></table>

{% hint style="info" %}
💡 Rewards will be distributed in APT based on USD value.
{% endhint %}

### Creator Tutorial

#### a. **Step-by-step guide**

{% embed url="<https://youtu.be/30ZQ2sqbnA8>" %}

{% hint style="info" %}

1. **New credit limit:** Only 0.1 credit is now required to submit a job (previously 1).
2. To claim credit from the daily check-ins, you will need APT to cover the gas fee.

👉 Get free **testnet APT** from the faucet here: <https://aptos.dev/network/faucet>

💡 <mark style="color:yellow;">`Log in with Google`</mark> >> <mark style="color:yellow;">`Enter your wallet address`</mark> >> <mark style="color:yellow;">`Click "Mint".`</mark>
{% endhint %}

#### **b. Earning Breakdown**

<table><thead><tr><th width="299.6363525390625" valign="middle">Task</th><th width="209.63641357421875" align="center" valign="middle">Point</th><th width="120" align="center">Credit</th></tr></thead><tbody><tr><td valign="middle">Claim credits in the Rewards section after completing eligible tasks.</td><td align="center" valign="middle"></td><td align="center"><a data-footnote-ref href="#user-content-fn-1"><strong>10</strong></a></td></tr><tr><td valign="middle">Complete a valid rendering job.</td><td align="center" valign="middle"><span class="math">{\footnotesize \text{Render Cost}  *  2.2 }</span></td><td align="center"></td></tr></tbody></table>

### Worker Tutorial

#### **a. Step-by-step guide**

{% embed url="<https://youtu.be/d2CtPZbCIFU>" %}
How to run a Worker node with the Pictor Worker app
{% endembed %}

{% hint style="info" %}
**Important notes**:

* To receive render tasks assigned from the network, your Worker must have **Blender installed**.
* To ensure rendering works properly, make sure your GPU has the correct and up-to-date driver installed. Select the correct driver for your GPU model 👇

👉 **NVIDIA (studio drivers):** <https://www.nvidia.com/en-us/drivers/>

👉 **AMD:** <https://www.amd.com/en/support/download/drivers.html>
{% endhint %}

#### **Docker Image Tutorial**

Besides the Worker app, you can now run Pictor Worker via a Docker image on Ubuntu Linux and Windows. To set it up, follow the steps below 👇:

{% tabs %}
{% tab title="🔶 On Ubuntu Linux" %}
{% hint style="warning" %}
**Requirements:**

1. A machine with an **NVIDIA GPU**.
2. **NVIDIA Container Toolkit** installed.

If you don’t have NVIDIA Container Toolkit installed, you can:

* Follow the [official NVIDIA guide](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
* Alternatively, use [Pictor's installation script](https://github.com/pictor-network/pictor-docker-install/blob/main/install-gpu-nvidia.sh) for the NVIDIA Container Toolkit
  {% endhint %}

**Step 1: Download the Worker Config File**

* Go to [testnet.pictor.network](https://testnet.pictor.network) >> My Workers >> create a new Worker.
* Download the Worker config file (`.json`) to your machine.

For example, save it at `/home/ubuntu/worker-config.json`

<figure><img src="/files/9kI2aI9b66hu7DOuEkot" alt=""><figcaption></figcaption></figure>

**Step 2: Install the Pictor Docker Image**

{% stepper %}
{% step %}
Download [Pictor's Docker Image installation script](https://github.com/pictor-network/pictor-docker-install/blob/main/install-worker.sh)

Ex., save it at `/home/ubuntu/install-worker.sh`
{% endstep %}

{% step %}
Grant execution permissions

{% code fullWidth="false" %}

```bash
chmod +x /home/ubuntu/install-worker.sh
```

{% endcode %}
{% endstep %}

{% step %}
Run the installation script

```bash
/home/ubuntu/install-worker.sh
```

When prompted, enter the **full path** to your Worker config file from Step 1.

```
/home/ubuntu/worker-config.json
```

{% endstep %}
{% endstepper %}

Your Pictor Worker is now running via Docker and connected to the Pictor Network, ready to process jobs.
{% endtab %}

{% tab title="🔶 On Windows" %}
{% hint style="warning" %}
**Requirements:**

1. A machine with an **NVIDIA GPU**.
2. **Docker Desktop is installed**. Follow this [official Docker guide](https://docs.docker.com/desktop/setup/install/windows-install/) if you haven't installed it yet.
   {% endhint %}

**Step 1: Download the Worker Config File**

* Go to [testnet.pictor.network](https://testnet.pictor.network) >> My Workers >> create a new Worker.
* Download the Worker config file (`.json`) to your machine.

For example, save it at `C:\Users\pictornetwork\worker-config.json`

<figure><img src="/files/9kI2aI9b66hu7DOuEkot" alt=""><figcaption></figcaption></figure>

**Step 2: Install the Pictor Docker Image**

{% stepper %}
{% step %}
Download Pictor's Docker Image installation scripts

* [run-install-worker.bat](https://github.com/pictor-network/pictor-docker-install/blob/main/run-install-worker.bat)
* [install-worker.ps1](https://github.com/pictor-network/pictor-docker-install/blob/main/install-worker.ps1)
  {% endstep %}

{% step %}
Run script

Find the `run-install-worker.bat` script >> Right-click, choose <mark style="color:yellow;">`Run as administrator`</mark>&#x20;
{% endstep %}

{% step %}
When prompted, enter the **full path** to your Worker config file from Step 1.

For example:&#x20;

```
C:\Users\pictornetwork\worker-config.json
```

{% endstep %}
{% endstepper %}

Your Pictor Worker is now running via Docker Desktop and connected to the Pictor Network, ready to process jobs.
{% endtab %}
{% endtabs %}

#### **b. Supported GPUs**

Check if your GPU is supported.

<details>

<summary><img src="/files/erM7xQSUZHdKfWsTxcbw" alt="" data-size="line">  NVIDIA </summary>

<table><thead><tr><th width="444">GPU Model</th><th>Performance Multiplier (24h)</th></tr></thead><tbody><tr><td>NVIDIA RTX PRO 6000 Blackwell Workstation Edition</td><td>11.5436</td></tr><tr><td>NVIDIA RTX PRO 6000 X Blackwell Generation</td><td>11.3564</td></tr><tr><td>NVIDIA GeForce RTX 5090</td><td>10.6878</td></tr><tr><td>NVIDIA GeForce RTX 5090 D</td><td>10.6466</td></tr><tr><td>NVIDIA GeForce RTX 4090</td><td>8.4265</td></tr><tr><td>NVIDIA RTX 6000 Ada Generation</td><td>7.621</td></tr><tr><td>NVIDIA GeForce RTX 4090 D</td><td>7.5827</td></tr><tr><td>NVIDIA GeForce RTX 5080</td><td>6.497</td></tr><tr><td>NVIDIA GeForce RTX 4080</td><td>6.2666</td></tr><tr><td>NVIDIA L40S</td><td>6.2016</td></tr><tr><td>NVIDIA GeForce RTX 4080 SUPER</td><td>5.9994</td></tr><tr><td>NVIDIA GeForce RTX 5090 Laptop GPU</td><td>5.6773</td></tr><tr><td>NVIDIA RTX 5000 Ada Generation</td><td>5.4844</td></tr><tr><td>NVIDIA RTX6000-Ada-12Q</td><td>5.4058</td></tr><tr><td>NVIDIA GeForce RTX 5070 Ti</td><td>5.3779</td></tr><tr><td>NVIDIA GeForce RTX 4090 Laptop GPU</td><td>5.0771</td></tr><tr><td>NVIDIA GeForce RTX 4070 Ti SUPER</td><td>5.0377</td></tr><tr><td>NVIDIA GeForce RTX 5080 Laptop GPU</td><td>4.8868</td></tr><tr><td>NVIDIA GeForce RTX 4070 Ti</td><td>4.7902</td></tr><tr><td>NVIDIA GeForce RTX 5070</td><td>4.3925</td></tr><tr><td>NVIDIA GeForce RTX 4070 SUPER</td><td>4.3719</td></tr><tr><td>NVIDIA GeForce RTX 3090 Ti</td><td>4.2985</td></tr><tr><td>NVIDIA GeForce RTX 3090</td><td>4.1984</td></tr><tr><td>NVIDIA GeForce RTX 3080 Ti</td><td>3.9898</td></tr><tr><td>NVIDIA RTX 5000 Ada Generation Laptop GPU</td><td>3.9254</td></tr><tr><td>NVIDIA RTX 4500 Ada Generation</td><td>3.9147</td></tr><tr><td>NVIDIA GeForce RTX 4080 Laptop GPU</td><td>3.9039</td></tr><tr><td>NVIDIA GeForce RTX 4070</td><td>3.8699</td></tr><tr><td>NVIDIA RTX A6000</td><td>3.7526</td></tr><tr><td>NVIDIA GeForce RTX 5070 Ti Laptop GPU</td><td>3.6737</td></tr><tr><td>NVIDIA RTX A5500</td><td>3.5407</td></tr><tr><td>NVIDIA RTX 4000 Ada Generation Laptop GPU</td><td>3.4787</td></tr><tr><td>NVIDIA GeForce RTX 3080</td><td>3.458</td></tr><tr><td>NVIDIA RTX A5000</td><td>3.3374</td></tr><tr><td>NVIDIA RTX 4000 Ada Generation</td><td>3.148</td></tr><tr><td>NVIDIA GeForce RTX 5060 Ti</td><td>3.1021</td></tr><tr><td>NVIDIA RTX 3500 Ada Generation Laptop GPU</td><td>3.068</td></tr><tr><td>NVIDIA RTX 4000 SFF Ada Generation</td><td>2.9268</td></tr><tr><td>NVIDIA GeForce RTX 5070 Laptop GPU</td><td>2.9094</td></tr><tr><td>NVIDIA RTX A4500</td><td>2.8781</td></tr><tr><td>NVIDIA A40</td><td>2.8579</td></tr><tr><td>NVIDIA GeForce RTX 4060 Ti</td><td>2.721</td></tr><tr><td>NVIDIA GeForce RTX 3070 Ti</td><td>2.6927</td></tr><tr><td>NVIDIA GeForce RTX 5060</td><td>2.624</td></tr><tr><td>NVIDIA GeForce RTX 4070 Laptop GPU</td><td>2.5588</td></tr><tr><td>NVIDIA GeForce RTX 5060 Laptop GPU</td><td>2.5548</td></tr><tr><td>NVIDIA GeForce RTX 3080 Ti Laptop GPU</td><td>2.4997</td></tr><tr><td>NVIDIA GeForce RTX 3070</td><td>2.4294</td></tr><tr><td>NVIDIA L4-12Q</td><td>2.3985</td></tr><tr><td>NVIDIA L4</td><td>2.383</td></tr><tr><td>NVIDIA GeForce RTX 4060 Laptop GPU</td><td>2.3673</td></tr><tr><td>NVIDIA GeForce RTX 3080 Laptop GPU</td><td>2.3558</td></tr><tr><td>NVIDIA TITAN RTX</td><td>2.2957</td></tr><tr><td>NVIDIA A10G</td><td>2.2868</td></tr><tr><td>NVIDIA RTX A4000</td><td>2.2647</td></tr><tr><td>NVIDIA RTX A5500 Laptop GPU</td><td>2.2611</td></tr><tr><td>NVIDIA GeForce RTX 3070 Ti Laptop GPU</td><td>2.2376</td></tr><tr><td>NVIDIA GeForce RTX 4060</td><td>2.2224</td></tr><tr><td>NVIDIA GeForce RTX 2080 Ti</td><td>2.1866</td></tr><tr><td>NVIDIA GeForce RTX 3060 Ti</td><td>2.1546</td></tr><tr><td>NVIDIA GeForce RTX 3070 Laptop GPU</td><td>2.1448</td></tr><tr><td>NVIDIA RTX A5000 Laptop GPU</td><td>2.1341</td></tr><tr><td>NVIDIA RTX 3000 Ada Generation Laptop GPU</td><td>2.0911</td></tr><tr><td>NVIDIA Quadro RTX 6000</td><td>2.0895</td></tr><tr><td>NVIDIA Quadro RTX 8000</td><td>2.0287</td></tr><tr><td>NVIDIA RTX 2000 Ada Generation</td><td>1.8884</td></tr><tr><td>NVIDIA GeForce RTX 4050 Laptop GPU</td><td>1.8378</td></tr><tr><td>NVIDIA RTX 2000 Ada Generation Laptop GPU</td><td>1.7756</td></tr><tr><td>NVIDIA GeForce RTX 2080 SUPER</td><td>1.7124</td></tr><tr><td>NVIDIA GeForce RTX 2070 SUPER</td><td>1.697</td></tr><tr><td>NVIDIA GeForce RTX 3060 Laptop GPU</td><td>1.6851</td></tr><tr><td>NVIDIA GeForce RTX 3060</td><td>1.6793</td></tr><tr><td>NVIDIA GeForce RTX 2080</td><td>1.6743</td></tr><tr><td>NVIDIA RTX A4500 Laptop GPU</td><td>1.6577</td></tr><tr><td>NVIDIA Tesla V100-SXM2-16GB</td><td>1.6171</td></tr><tr><td>NVIDIA GeForce RTX 2060 SUPER</td><td>1.5927</td></tr><tr><td>NVIDIA GeForce RTX 2070</td><td>1.5805</td></tr><tr><td>NVIDIA Quadro RTX 4000</td><td>1.5598</td></tr><tr><td>NVIDIA RTX A3000 12GB Laptop GPU</td><td>1.5433</td></tr><tr><td>NVIDIA RTX 1000 Ada Generation Laptop GPU</td><td>1.5316</td></tr><tr><td>NVIDIA Quadro RTX 5000</td><td>1.5123</td></tr><tr><td>NVIDIA RTX A3000 Laptop GPU</td><td>1.4262</td></tr><tr><td>NVIDIA GeForce RTX 2070 Super with Max-Q Design</td><td>1.322</td></tr><tr><td>NVIDIA GeForce RTX 2080 Super with Max-Q Design</td><td>1.3216</td></tr><tr><td>NVIDIA TITAN V</td><td>1.3138</td></tr><tr><td>NVIDIA RTX A2000 12GB</td><td>1.3133</td></tr><tr><td>NVIDIA GeForce RTX 2070 with Max-Q Design</td><td>1.2848</td></tr><tr><td>NVIDIA GeForce RTX 2060</td><td>1.1703</td></tr><tr><td>NVIDIA RTX 500 Ada Generation Laptop GPU</td><td>1.1641</td></tr><tr><td>NVIDIA GeForce RTX 2080 with Max-Q Design</td><td>1.1225</td></tr><tr><td>NVIDIA Quadro RTX 3000</td><td>1.1097</td></tr><tr><td>NVIDIA Quadro RTX 5000 with Max-Q Design</td><td>1.1013</td></tr><tr><td>NVIDIA GeForce RTX 3050</td><td>1.0757</td></tr><tr><td>NVIDIA Tesla T4</td><td>1.0312</td></tr><tr><td>NVIDIA GeForce RTX 2060 with Max-Q Design</td><td>1.004</td></tr><tr><td>NVIDIA GeForce RTX 3050 OEM</td><td>0.997</td></tr><tr><td>NVIDIA GeForce RTX 3050 Ti Laptop GPU</td><td>0.9553</td></tr><tr><td>NVIDIA RTX A2000 8GB Laptop GPU</td><td>0.9219</td></tr><tr><td>NVIDIA RTX A2000 Laptop GPU</td><td>0.8808</td></tr><tr><td>NVIDIA CMP 40HX</td><td>0.8484</td></tr><tr><td>NVIDIA GeForce RTX 3050 Laptop GPU</td><td>0.844</td></tr><tr><td>NVIDIA GeForce RTX 3050 6GB Laptop GPU</td><td>0.8147</td></tr><tr><td>NVIDIA RTX A1000 6GB Laptop GPU</td><td>0.7197</td></tr><tr><td>NVIDIA TITAN Xp</td><td>0.677</td></tr><tr><td>NVIDIA GeForce GTX 1080 Ti</td><td>0.6161</td></tr><tr><td>NVIDIA TITAN X (Pascal)</td><td>0.5975</td></tr><tr><td>NVIDIA P102-100</td><td>0.5939</td></tr><tr><td>NVIDIA GeForce GTX 1660 Ti</td><td>0.5747</td></tr><tr><td>NVIDIA Tesla P40</td><td>0.5649</td></tr><tr><td>NVIDIA GeForce GTX 1660 SUPER</td><td>0.5586</td></tr><tr><td>NVIDIA Quadro P6000</td><td>0.5564</td></tr><tr><td>NVIDIA GeForce GTX 1660 Ti with Max-Q Design</td><td>0.5454</td></tr><tr><td>NVIDIA GeForce RTX 2050</td><td>0.5347</td></tr><tr><td>NVIDIA GeForce GTX 1660</td><td>0.5169</td></tr><tr><td>NVIDIA GeForce RTX 3050 4GB Laptop GPU</td><td>0.4967</td></tr><tr><td>NVIDIA GeForce GTX 1070 Ti</td><td>0.4513</td></tr><tr><td>NVIDIA P104-100</td><td>0.4419</td></tr><tr><td>NVIDIA GeForce GTX 1080</td><td>0.433</td></tr><tr><td>NVIDIA Quadro P5200</td><td>0.407</td></tr><tr><td>NVIDIA GeForce GTX 1070</td><td>0.4002</td></tr><tr><td>NVIDIA GeForce GTX TITAN X</td><td>0.3977</td></tr><tr><td>NVIDIA GeForce GTX 1650 SUPER</td><td>0.3964</td></tr><tr><td>NVIDIA Quadro P5000</td><td>0.3869</td></tr></tbody></table>

</details>

<details>

<summary><img src="/files/2Of34dw1w1dRsnHHnTsv" alt="" data-size="line">  AMD</summary>

| GPU Model                  | Performance Multiplier (24h) |
| -------------------------- | ---------------------------- |
| AMD Radeon RX 7900 XTX     | 2.8573                       |
| AMD Radeon PRO W7900       | 2.5522                       |
| AMD Radeon RX 7900 XT      | 2.5212                       |
| AMD Radeon RX 9070 XT      | 2.2173                       |
| AMD Radeon RX 7900 GRE     | 1.9887                       |
| AMD Radeon RX 6950 XT      | 1.9687                       |
| AMD Radeon RX 9070         | 1.9466                       |
| AMD Radeon PRO W7800       | 1.8566                       |
| AMD Radeon RX 6900 XT      | 1.835                        |
| AMD Radeon RX 6800 XT      | 1.765                        |
| AMD Radeon RX 7800 XT      | 1.7256                       |
| AMD Radeon RX 7700 XT      | 1.4945                       |
| AMD Radeon RX 6800         | 1.3667                       |
| AMD Radeon PRO W6800       | 1.2831                       |
| AMD Radeon RX 6750 XT      | 1.1516                       |
| AMD Radeon RX 9060 XT      | 1.1255                       |
| AMD Radeon RX 6700 XT      | 1.0853                       |
| AMD Radeon RX 6800M        | 0.9993                       |
| AMD Radeon RX 7600         | 0.9245                       |
| AMD Radeon RX 7600 XT      | 0.9155                       |
| AMD Radeon PRO W7600       | 0.8768                       |
| AMD Radeon RX 7700S        | 0.8173                       |
| AMD Radeon RX 6650 XT      | 0.8162                       |
| AMD Radeon RX 6600 XT      | 0.7819                       |
| AMD Radeon RX 7600M XT     | 0.7507                       |
| AMD Radeon RX 7600S        | 0.7435                       |
| AMD Radeon RX 5700 XT      | 0.7085                       |
| AMD Radeon RX 6600         | 0.7017                       |
| AMD Radeon RX 6600M        | 0.6368                       |
| AMD Radeon RX 5700         | 0.6303                       |
| AMD Radeon RX 5600M Series | 0.438                        |
| AMD Radeon RX 5600 XT      | 0.4368                       |
| AMD Radeon Pro W5500       | 0.3567                       |
| AMD Radeon RX 6500 XT      | 0.3159                       |

</details>

<details>

<summary><img src="/files/JNTV6fOm5UN9f5dzVgK6" alt="" data-size="line">  APPLE</summary>

{% hint style="info" %}
The following GPUs will be supported very soon.
{% endhint %}

| GPU Model                       | Performance Multiplier (24h) |
| ------------------------------- | ---------------------------- |
| Apple M3 Ultra (GPU - 80 cores) | 5.2213                       |
| Apple M3 Ultra (GPU - 60 cores) | 4.6081                       |
| Apple M4 Max (GPU - 40 cores)   | 3.7155                       |
| Apple M4 Max (GPU - 32 cores)   | 3.1633                       |
| Apple M3 Max (GPU - 40 cores)   | 3.0082                       |
| Apple M3 Max (GPU - 30 cores)   | 2.4422                       |
| Apple M4 Pro (GPU - 20 cores)   | 1.7959                       |
| Apple M4 Pro (GPU - 16 cores)   | 1.6874                       |
| Apple M3 Pro (GPU - 18 cores)   | 1.2504                       |
| Apple M3 Pro (GPU - 14 cores)   | 1.1774                       |
| Apple M4 (GPU - 8 cores)        | 0.7525                       |
| Apple M4 (GPU - 10 cores)       | 0.7524                       |
| Apple M3 (GPU - 10 cores)       | 0.6491                       |
| Apple M3 (GPU - 8 cores)        | 0.6452                       |

</details>

{% hint style="info" %}
**Notes:**

* **Performance Multiplier (P)**: Each GPU has a different Performance Multiplier (24h). The more powerful your GPU, the higher the multiplier, meaning more points per hour of online time.
* The list of supported GPUs may change during the campaign based on performance, stability, or network conditions.
  {% endhint %}

#### **c. Earning Breakdown**

<table><thead><tr><th width="400.272705078125">Task</th><th width="275" align="center">Point </th></tr></thead><tbody><tr><td><p><strong>Render</strong>: </p><p>Install, run the Worker app, and render assigned tasks</p></td><td align="center"><span class="math">{\footnotesize \displaystyle\frac{\text{Completed Tasks} * \text{Render Cost} * 4}{\text{Job's Total Tasks}} }  </span></td></tr><tr><td><p><strong>Online</strong>: </p><p>Install and turn on the Worker app, but do not render tasks</p></td><td align="center"><span class="math">{\footnotesize \displaystyle\frac{O * P}{24} }</span></td></tr></tbody></table>

{% hint style="info" %}
**O: Online Time -** Time that the Worker Node is online, but does not render tasks.

**P: Performance Multiplier -** Based on your GPU’s Blender benchmark score.
{% endhint %}

{% hint style="info" %}
**Example**:&#x20;

Let’s say you have a dual-GPU device:

* An <mark style="color:yellow;">`RTX 3070`</mark> with a Performance Multiplier (P) of <mark style="color:yellow;">`2.4294`</mark>.&#x20;
* An <mark style="color:yellow;">`RTX 5090`</mark> with a Performance Multiplier (P) of <mark style="color:yellow;">`10.6878`</mark>.

You spent:&#x20;

* 6 hours online, but not rendering  (<mark style="color:yellow;">`O = 6`</mark>)

Your points for that session are: <mark style="color:yellow;">`Points = 6 * (2.4294 + 10.6878) / 24 =`</mark><mark style="color:yellow;">` `</mark><mark style="color:yellow;">**`3.2793`**</mark>
{% endhint %}

### Community Member Tutorial

Everyone can earn extra points by supporting the Pictor Testnet through community actions, whether you're a Creator, a Worker, or just here to explore.

Complete the following tasks to boost your points and climb the Leaderboard.

**a. Daily check-in**

<details>

<summary><strong>Daily check-in rewards</strong></summary>

<table><thead><tr><th width="200">Day</th><th width="100" align="center">Point</th><th width="100" align="center">Credit</th></tr></thead><tbody><tr><td>Day 1</td><td align="center">1</td><td align="center"></td></tr><tr><td>Day 2</td><td align="center">2</td><td align="center"></td></tr><tr><td>Day 3</td><td align="center">3</td><td align="center"></td></tr><tr><td>Day 4</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 5</td><td align="center">2</td><td align="center"></td></tr><tr><td>Day 6</td><td align="center">3</td><td align="center"></td></tr><tr><td>Day 7</td><td align="center">4</td><td align="center"></td></tr><tr><td>Day 8</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 9</td><td align="center">3</td><td align="center"></td></tr><tr><td>Day 10</td><td align="center">4</td><td align="center"></td></tr><tr><td>Day 11</td><td align="center">5</td><td align="center"></td></tr><tr><td>Day 12</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 13</td><td align="center">4</td><td align="center"></td></tr><tr><td>Day 14</td><td align="center">5</td><td align="center"></td></tr><tr><td>Day 15</td><td align="center">6</td><td align="center"></td></tr><tr><td>Day 16</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 17</td><td align="center">5</td><td align="center"></td></tr><tr><td>Day 18</td><td align="center">6</td><td align="center"></td></tr><tr><td>Day 19</td><td align="center">7</td><td align="center"></td></tr><tr><td>Day 20</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 21</td><td align="center">6</td><td align="center"></td></tr><tr><td>Day 22</td><td align="center">7</td><td align="center"></td></tr><tr><td>Day 23</td><td align="center">8</td><td align="center"></td></tr><tr><td>Day 24</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 25</td><td align="center">7</td><td align="center"></td></tr><tr><td>Day 26</td><td align="center">8</td><td align="center"></td></tr><tr><td>Day 27</td><td align="center">9</td><td align="center"></td></tr><tr><td>Day 28</td><td align="center"></td><td align="center">1</td></tr><tr><td>Day 29</td><td align="center">9</td><td align="center"></td></tr><tr><td>Day 30</td><td align="center">10</td><td align="center"></td></tr></tbody></table>

</details>

**b. Social tasks**

<table><thead><tr><th width="418.3636474609375">Task</th><th width="260.181884765625" align="center">Point</th></tr></thead><tbody><tr><td>Follow Pictor Network on X</td><td align="center">5</td></tr><tr><td>Join Pictor Network’s Official Channel on Telegram</td><td align="center"><strong>5</strong></td></tr><tr><td>Join Pictor Network’s Official Community on Telegram</td><td align="center"><strong>5</strong></td></tr><tr><td>Follow Pictor Network on LinkedIn</td><td align="center"><strong>5</strong></td></tr><tr><td>Subscribe Pictor Network YouTube channel</td><td align="center"><strong>5</strong></td></tr></tbody></table>

**c. Referral**

Invite friends to join the Pictor Network Testnet campaign. The referrer will earn **10%** of all the referee’s points.

## Rules

**No automation & cheating**: \
Participants are strictly prohibited from using bots, scripts, hacks, or any tools to cheat or manipulate the system. Anyone found faking activity, exploiting bugs, or attempting to gain an unfair advantage will be immediately disqualified, will forfeit all current and future rewards, and will be permanently banned from this testnet campaign.

## Disclaimer

1. **Testnet Environment:** This is a **pre-production testing environment**. Performance, availability, and network stability may vary during the campaign. Unexpected bugs, crashes, or job failures may occur and should be expected.
2. **Activity Auditing:** The Pictor team reserves the right to **review and audit** user activity at any time.\
   Suspicious behavior, abuse, or violation of campaign rules may result in the removal of points and rewards or an account ban.
3. **Terms May Change:** Pictor may update the campaign terms at any time, such as task types, point & reward calculations. Please follow official Pictor channels to stay informed and avoid missing important updates.
4. **Final Decisions:** All decisions related to the campaign, including task validation, reward adjustments, rule interpretations, and dispute resolutions, are at the sole discretion of the Pictor team and are considered final.
5. **Security:** For your safety, **never share your private key or seed phrase** with anyone. The Pictor team will **never DM you first** under any circumstances.

## FAQs

<details>

<summary>🔹 What are points? How do they work?</summary>

* Points are your testnet scores that reflect how actively and reliably you contribute.&#x20;
* Points determine your leaderboard rank and will be kept until TGE for more benefits.

</details>

<details>

<summary>🔹 What are credits? How do I get them?</summary>

* Credits are what you use to pay for jobs on Pictor Network.
* You can earn free credits by completing tasks in the Rewards section or by depositing USDT in the **Credit** section (coming soon).

{% hint style="info" %}

* You need at least 0.1 credit to submit a rendering job.
* Claiming credits from daily check-ins is on-chain, and you'll need a small amount of **testnet APT** to cover the gas fee.
  {% endhint %}

</details>

<details>

<summary>🔹 Is there a leaderboard? How is the ranking calculated?</summary>

Yes. The leaderboard displays the top participants in the testnet campaign, ranked by their total Points.

</details>

<details>

<summary>🔹 What rewards will the leaderboard winners receive?</summary>

The **top 100 users** on the leaderboard will **share a reward pool of $2,000 worth of APT**. Rewards will be allocated based on your final ranking when the testnet ends.&#x20;

👉 See reward breakdown [here](https://docs.pictor.network/docs/campaign/testnet-on-aptos#general-guide).

</details>

<details>

<summary>🔹 What GPUs are supported for running as a Worker?</summary>

We support a wide range of **NVIDIA, AMD, and Apple** GPUs.

View the full GPU list here:

* NVIDIA: <https://docs.pictor.network/docs/network/testnet#nvidia>
* AMD: <https://docs.pictor.network/docs/network/testnet#amd>
* Apple: <https://docs.pictor.network/docs/network/testnet#apple>

</details>

<details>

<summary>🔹 How can I run a Worker node on Pictor Network?</summary>

You can run a Worker node in two ways:

1. **Worker App** (*Windows only*) – Install the app, import your Worker config file, and connect.
2. Docker Image (*Ubuntu Linux & Windows with NVIDIA GPU*) – Follow [this guide](https://docs.pictor.network/docs/network/testnet#docker-image-tutorial) to set it up.

</details>

<details>

<summary>🔹 Can I run more than one Worker under one Pictor account?</summary>

Yes, you can run **multiple Workers** using **one Pictor account**.<br>

</details>

<details>

<summary>🔹 My worker app is running, but not receiving jobs — what should I do?</summary>

If you use the Pictor Worker app, you must manually **install Blender** to receive rendering tasks from Pictor.

To fix this:

1. Open the Pictor **Worker App**
2. Go to the **Settings** tab
3. Select a Blender version (we recommend the latest, e.g., **4.4**) and install it
4. After installation, click the **Detect** button so the app can recognize Blender

Once detected, your worker will be ready to receive tasks as they come in.

</details>

<details>

<summary>🔹 Why is my Worker rendering with CPU instead of GPU?</summary>

In some cases, your Worker automatically switches to **using the CPU instead of the GPU** to render a task. This results in significantly lower performance and longer render times, negatively impacting workers' experiences.

Possible Reasons:

* **Weak GPU:**\
  If your GPU lacks sufficient VRAM or does not meet the minimum compute capability required for certain render tasks, Blender may fall back to CPU rendering.
* **Tasks containing Python scripts** (<mark style="color:yellow;">**`.py`**</mark> )**:**\
  Some tasks include Python scripts (e.g., for customizing materials, animations, or rendering logic). These scripts are not yet supported by the GPU rendering pipeline, and such tasks will automatically run on the CPU.

{% hint style="warning" %}

* We are continuing to investigate and will provide appropriate solutions in upcoming app updates.
* Keep an eye on our [Discord](https://discord.gg/5RHMK9xF4x) channel so you won't miss the update notification.
  {% endhint %}

</details>

<details>

<summary>🔹Why does my Worker app display the message "Worker MAC address exists?"</summary>

Each Worker is linked to the MAC address of the device it was first registered. This means a single device can only be associated with **one Worker at a time**. If you're trying to create or connect a new Worker on the same device, the system will detect that the MAC address is already in use and show this error.

To fix it:

1. Go to the Testnet dashboard
2. Navigate to **My Workers**
3. Find and **delete the existing Worker** that uses this MAC address
4. You can now connect the new Worker to this device

</details>

<details>

<summary>🔹 Where can I get help or report issues?</summary>

You can get help by chatting directly in our [Telegram](https://t.me/pictor_community) channel or by opening a support ticket in the `#🎫・ticket channel` on our [Discord](https://discord.gg/5RHMK9xF4x).

Our community moderators and support staff are ready to assist you on both platforms.

</details>

[^1]: You can earn up to 10 credits by completing all the tasks in the Rewards section.


---

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