Testnet on Aptos

The Pictor Network Testnet is now live on Aptos. Discover multiple ways to participate and earn rewards 👇

Testnet Campaign Overview

The Pictor Network Testnet on Aptos is now live, and anyone can join. This is your chance to try out a real decentralized GPU network, help improve it, and earn rewards while doing so.

Important Information:

1. 🌐Testnet page: https://testnet.pictor.network/

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.

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, 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.

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.

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 Nodes 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 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:

🏆 Rank	💰 Total Reward (in APT)	💸 Reward per User (in APT)
#1	$200	$200
#2–5	$400	$100
#6–15	$500	$50
#16–50	$500	$14
#51–100	$400	$8

💡 Rewards will be distributed in APT based on USD value.

Creator Tutorial

a. Step-by-step guide

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

💡 Log in with Google >> Enter your wallet address >> Click "Mint".

b. Earning Breakdown

Task	Point	Credit
Claim credits in the Rewards section after completing eligible tasks.
Complete a valid rendering job.	${\footnotesize \text{Render Cost} * 2.2 }$

Worker Tutorial

a. Step-by-step guide

How to run a Worker node with the Pictor Worker app

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

Docker Image Tutorial

Besides the Worker app, you can now run Pictor Worker via a Docker image on Ubuntu Linux. Set it up, following the steps below 👇:

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

• Alternatively, download Pictor's install script

Step 1: Download the Worker Config File

• Go to testnet.pictor.network >> My Nodes >> create a new Worker.

• Download the Worker config file (.json) to your machine.

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

Step 2: Install the Pictor Docker Image

1

Download Pictor's installation script

Ex., save it at /home/ubuntu/install-worker.sh

2

Grant execution permissions

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

3

Run the installation script

/home/ubuntu/install-worker.sh

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

/home/ubuntu/worker-config.json

Your Pictor Worker is now running via Docker and connected to the Pictor Network, ready to start processing jobs.

b. Supported GPUs

Check if your GPU is supported.

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

APPLE

The following GPUs will be supported very soon.

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

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.

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

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.

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

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

Daily check-in rewards

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

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
More Tasks	Tasks are updated regularly

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

🔹 What are points? How do they work?

• Points are your testnet scores that reflect how actively and reliably you contribute.

• Points determine your leaderboard rank and will be kept until TGE for more benefits.

🔹 What are credits? How do I get them?

• 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).

• 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.

🔹 Is there a leaderboard? How is the ranking calculated?

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

🔹 What rewards will the leaderboard winners receive?

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.

👉 See reward breakdown here.

🔹 What GPUs are supported for running as a Worker?

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

View the full GPU list here:

• NVIDIA: https://docs.pictor.network/docs/campaign/testnet-on-aptos#nvidia

• AMD: https://docs.pictor.network/docs/campaign/testnet-on-aptos#amd

• Apple: https://docs.pictor.network/docs/campaign/testnet-on-aptos#apple

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

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 with NVIDIA GPU) – Get your Worker config file, run the installation script, and your node is connected.

Docker Image is coming soon!

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

Yes, you can run multiple Workers using one Pictor account.

🔹 My worker is online but not receiving jobs — what should I do?

Your worker needs Blender installed 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.

🔹 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.

• We are continuing to investigate and will provide appropriate solutions in upcoming app updates.

• Keep an eye on our Discord channel so you won't miss the update notification.

🔹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 Testnet dashboard

2. Navigate to My Nodes

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 channel or by opening a support ticket in the #🎫・ticket channel on our Discord.

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