Trading activity:
Reported 24-hour volume equals 0.11% of market capitalization. The local markets snapshot lists Gate, PancakeSwap (v2) and PancakeSwap V3 (BSC) among venues with observed trading activity.
YearBull indicators:
YearBull Rank #2,505. Bull Score 61/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h 1.42% · 7d 0.81% · 30d -11.89%.
Values are descriptive and should be read together rather than as a price forecast.
Read the YearBull methodology.
Snapshot date: 2026-10-27.Data history: 90 days available in the latest 90-day window.
Methodology responsibility:
YearBull’s analytical methodology and presentation rules are developed and maintained by
Alan Zelvin, Founder & Lead Crypto Researcher.
This note identifies responsibility for the methodology; it does not attribute authorship of this data snapshot.
What is NetMind Token (NMT)?
Source description
“NetMind Power leverages the underutilized or idle GPUs of users worldwide, creating a global network of computing power. This approach addresses the monopolistic control in the computing sector by harnessing a vast, untapped resource. Many individuals own GPUs for activities like gaming, video rendering, or crypto mining, which often remain underutilized. NetMind Power utilizes these GPUs, offering a solution that benefits both GPU owners and the AI community. The platform integrates large-scale distributed computing, incorporating grid computing, voluntary computing scheduling, and load balancing technologies. It provides a low-latency, well-connected, and easy-to-manage environment for distributed deep learning training and inference. The core components of NetMind Power include a training platform, an inference platform, and the NetMind Chain and Token (NMT). This utility token facilitates transactions within the platform. NetMind Power's innovative approach is particularly relevant in the current landscape, where AI has become a major technological advancement. The demand for high-performance computing is continuously rising, making access to necessary resources expensive and limited. By tapping into the pool of idle GPUs, NetMind Power offers a cost-effective and efficient solution for AI model training and inference.”
This source-supplied description may contain old, promotional, or unverified claims and is not YearBull editorial analysis.
Official links and contract records appear in Key Facts. Project details can change, so verify current information with the project.
NetMind Token (NMT) FAQ
How does NetMind Power use idle GPUs?
NetMind Power says it aggregates underutilized GPUs owned by users worldwide into a distributed computing network. These devices may otherwise sit unused after activities such as gaming, video rendering, or crypto mining. The project positions this model as a way to expand access to computing capacity while creating a role for GPU owners within the network.
What kinds of AI workloads does NetMind Power support?
The project presents its platform as supporting distributed deep-learning training and inference. It describes a low-latency, well-connected environment intended to help users run these workloads across participating computing resources. NetMind Power frames this approach as a response to the high cost and limited availability of conventional high-performance computing.
Which technologies does NetMind Power use to coordinate distributed computing?
NetMind Power says its infrastructure combines grid computing, voluntary computing scheduling, and load-balancing technologies. Together, these components are intended to coordinate participating GPUs and distribute workloads across them. The project presents this architecture as a way to manage a large, geographically dispersed pool of computing resources for AI-related tasks.
What are the main components of the NetMind Power platform?
The project identifies three core components: a training platform, an inference platform, and NetMind Chain and Token. The training and inference platforms correspond to its stated AI-computing functions, while NMT is presented as the utility token used for transactions within the platform. The project does not specify the full transaction or fee structure here.
Why does NetMind Power focus on decentralized access to computing power?
NetMind Power positions its model as an alternative to concentrated control over computing resources. By drawing on idle GPUs from many users, the project says it can create a broader pool of capacity for the AI community. It presents this approach as potentially more cost-effective and efficient than relying solely on scarce, centralized high-performance computing.
NetMind Token metric comparison
This comparison is a stored snapshot generated 2026-10-22 06:31 UTC from 291 daily observations available from 2025-12-30 through 2026-10-22. It is separate from the latest analytical cards above. Percentiles compare the snapshot value with that day's analytical universe; a higher percentile means a larger observed value, not necessarily a better investment characteristic.
Metric
Snapshot
30d before
90d before
Change vs 30d
Universe percentile
Price
$0.0421
$0.0473
$0.0421
-10.9%
n/a
Market cap
$2.74M
$3.03M
$2.61M
-9.4%
P75.1
YearBull Rank
#3,164
#3,549
#2,766
Improved 385
P62.9
Bull Score
60/100
58/100
47/100
+2.0 pts
P72.8
Turnover
0.08%
0.04%
0.27%
+0.0 pts
P27.8
YB Market Risk
Low
Low
Low
Unchanged
n/a
Cycle
Early
Early
Early
Unchanged
n/a
Median absolute daily movement 0.78%; distance from the highest local daily price -65.1%; circulating supply change +16.0%. These measurements are descriptive and do not predict future direction.
YearBull Rank overview
Current YearBull Rank for netmind-token: #2505.
Rank timeline (last 365 days)
Rank movement (nearest daily data).
Reading rule: smaller rank numbers are better.
7d window (2026-10-21): #2333 → #2505 (down by 172).
30d window (2026-09-28): #2631 → #2505 (up by 126).
Regime context: If the line stair-steps, the cycle may be driven by discrete inputs. a stable phase often tightens the rank range.
Liquidity note: If the line improves during quiet periods, it can be accumulation. relative rank is sensitive to who is active in the window.
Listing context: If the line breaks range, confirm it across a longer window. consolidation can make rank more stable.
Risk posture: If the curve is step-like, it may be reacting to discrete inputs. big jumps can be data-driven, but also rotation-driven.
YearBull Rank is a comparative index on YearBull that helps contextualize a coin’s position versus others over time. Smaller numbers mean the coin sits higher in the YearBull list.
Editorial note:
This analysis was prepared by the YearBull research team under the direction of
Alan Zelvin,
Founder and Lead Crypto Researcher.
The assessment follows YearBull’s internal research methodology and editorial standards.
Methodology ·
Editorial Policy
Related Research
Continue with contextually connected profiles and category data:
Venue refresh pending. Markets last checked: 2026-07-26. The next refresh is queued in the hourly updater. Venue listings and volumes are stored snapshots, not live quotes.
