# Mainnet ## Overview {% hint style="info" %} **Important Information**: 1. 🌐**Mainnet page**: [app.pictor.network](http://app.pictor.network/) 2. 🧩 Roles: Join as a **Creator, Worker** to earn points. You can also take on both roles to earn even more points for bigger rewards in the future. {% endhint %} ## How to Participate ### General Guide Getting started is easy. All roles follow the same steps as follows: **Step 1: Sign Up**:\ Visit the [app.pictor.network](http://app.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 or Worker**. * **Creator**: Go to the **Rendering** section, submit Blender rendering jobs for Workers in the network to process. * **Worker**: Go to the **My Workers** section, set up your Worker nodes, and start contributing your GPU power to the network. **Step 3: Start Earning Points**\ Complete tasks based on your role: * **Creator**: Claim free credits or buy 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. **Step 4: Track Your Earnings** View the total points and rewards you have earned directly in your dashboard. ### Creator Tutorial Follow this [detailed tutorial](https://docs.pictor.network/docs/services/3d-rendering/get-started) to get started. {% hint style="info" %} **Important Notes:** 1. **Free Credit**: To claim free credit from the daily check-ins, you will need APT to cover the transaction fee. 2. **Point Formula**: Render Cost \* 2.2 {% endhint %} ### Worker Tutorial #### **a. Supported GPUs** Please check if your GPU is supported before jumping into the detailed tutorial.

NVIDIA

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

AMD

| 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 |

{% hint style="warning" %} **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 based on performance, stability, or network conditions. {% endhint %} #### **b. Step-by-step guide** Follow this [detailed tutorial](https://docs.pictor.network/docs/gpu-providers/workers/get-started) to get started. #### **c. Earning Breakdown**

Task	Point
Render: Install, run the Worker app, and render assigned tasks	{\footnotesize \displaystyle\frac{\text{Completed Tasks} * \text{Render Cost} * 4}{\text{Job's Total Tasks}} }
Online: Install and turn on the Worker app, but do not render tasks	{\footnotesize \displaystyle\frac{O * P}{24} }

Task

Point

Render:

Install, run the Worker app, and render assigned tasks

{\footnotesize \displaystyle\frac{\text{Completed Tasks} * \text{Render Cost} * 4}{\text{Job's Total Tasks}} }

Online:

Install and turn on the Worker app, but do not render tasks

{\footnotesize \displaystyle\frac{O * P}{24} }

{% hint style="info" %} **Formula Symbols Explanation:** **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**: Let’s say you have a dual-GPU device: * An `RTX 3070` with a Performance Multiplier (P) of `2.4294`. * An `RTX 5090` with a Performance Multiplier (P) of `10.6878`. You spent: * 6 hours online, but not rendering (`O = 6`) Your points for that session are: `Points = 6 * (2.4294 + 10.6878) / 24 =`` `**`3.2793`** {% endhint %} ### Other Tasks Everyone can earn extra points by completing other tasks, whether you're a Creator, a Worker, or just here to explore. Complete the following tasks to boost your points. **a. Daily check-in**

Daily check-in rewards

Day	Point	Credit
Day 1		1
Day 2	1
Day 3	2
Day 4	3
Day 5	4
Day 6	5
Day 7		1
Day 8	2
Day 9	3
Day 10	4
Day 11	5
Day 12	6
Day 13		1
Day 14	3
Day 15	4
Day 16	5
Day 17	6
Day 18	7
Day 19		1
Day 20	4
Day 21	5
Day 22	6
Day 23	7
Day 24	8
Day 25		1
Day 26	5
Day 27	6
Day 28	7
Day 29	8
Day 30	9

**b. Social tasks**

Task	Point
Follow Pictor Network on X	5
Join Pictor Network’s Official Channel on Telegram	5
Join Pictor Network’s Official Community on Telegram	5
Follow Pictor Network on LinkedIn	5
Subscribe Pictor Network YouTube channel	5

**c. Referral** Invite friends to join the Pictor Network Mainnet. 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 Pictor Network. ## Disclaimer 1. **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. 2. **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. 3. **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. 4. **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

🔹 What are points? How do points in the mainnet work?

Points are scores that reflect your contribution to Pictor Network. * **Testnet points**: The points you earned during our testnet. These points are carried over in full to the mainnet phase. * **Mainnet points**: From launch, you will continue earning new points based on your mainnet activities. * Both points are **accumulated together**. At TGE, your total points will determine the benefits and rewards you receive.

🔹 What are credits? How do I get them?

* Credits are what you use to pay for computing services on Pictor Network. * You can claim free credits through the daily check-in task or buy them using USDT or Fiat in the **Credit** section. {% hint style="info" %} Claiming credits from daily check-ins is on-chain, and you'll need a small amount of **APT** to cover the transaction fee. {% endhint %}

🔹 What GPUs are supported for running as a Worker?

We support a wide range of **NVIDIA, and AMD** GPUs. View the full GPU list here: * NVIDIA: * AMD:

🔹 How can I run a Worker node on Pictor Network?

You can run a Worker node in two ways: 1. **Worker App** (*Windows only*) 2. **Docker Image** (*Ubuntu Linux & Windows with NVIDIA GPU*) Visit our [detailed guide](https://docs.pictor.network/docs/gpu-providers/workers/get-started) to get started.

🔹 Can I run more than one Worker node under one Pictor account?

Yes, you can run **multiple Worker nodes** using **one Pictor account**.

🔹 My worker desktop app is running, but not receiving jobs — what should I do?

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) 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.

🔹 Why is my Worker rendering with CPU instead of GPU?

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** (**`.py`** )**:**\ 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 %}

🔹Why does my Worker app display the message "Worker MAC address exists?"

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

🔹 Where can I get help or report issues?

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.