Trading activity:
Reported 24-hour volume equals 0.00% of market capitalization. The local markets snapshot lists PancakeSwap (v2) among venues with observed trading activity.
YearBull indicators:
YearBull Rank #8,850. Bull Score 27/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h 0.00% · 7d -6.57% · 30d -33.44%.
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 Raven Protocol (RAVEN)?
Source description
“Raven Protocol's specific use case is to perform AI training where speed is the key. We're taking a 1M image dataset that takes 2-3 weeks to train on AWS down to 2-3 hours on Raven. AI companies will be able to train models better and faster. Raven Protocol is creating a self-sustaining and dynamic ecosystem for: Customers who want to train their AI engines; and/or Contributors who would like to share their compute resources in the form of Computers, Smartphones, or even a server rack. Raven Tokens (RAVEN) will work as the common ground to facilitate a secure transaction that will take place inside our ecosystem. Enterprise clients who want to rent compute power will do so with RAVEN and contributors of the compute power will be rewarded in RAVEN. Raven is creating a network of compute nodes that utilize idle compute power for the purposes of AI training where speed is the key. A native token is the key to bootstrapping a nascent network. We want to incentivize and reward people all over the world to contribute their compute power to our network. Additionally, we will reward token holders for running masternodes which will be responsible for orchestrating the training of various deep neural networks. Our consensus mechanism is something we call Proof-of-Calculation. Proof-of-Calculation will be the primary guideline for the regulation and distribution of incentives to the compute nodes in the network. Following are the two prime deciders for the incentive distribution: Speed: Depending upon how fast a node can perform gradient calculations (in a neural network) and return it back to the Gradient Collector. Redundancy: The 3 fastest redundant calculation will only qualify for receiving the incentive.”
This source-supplied description may contain old, promotional, or unverified claims and is not YearBull editorial analysis.
Recorded networks: Binancecoin, Binance Smart Chain
Official links and contract records appear in Key Facts. Project details can change, so verify current information with the project.
Raven Protocol (RAVEN) FAQ
How does Raven Protocol describe its approach to accelerating AI training?
The project states that it uses a network of compute nodes to train AI models with idle processing capacity. Raven presents a 1 million-image training example in which work that reportedly takes two to three weeks on AWS could be reduced to two to three hours on its network. This speed claim is central to its proposed value for AI companies seeking faster model training.
Who can contribute computing resources to Raven Protocol’s network?
Raven describes an ecosystem with contributors who share available computing resources for AI training. These resources may include personal computers, smartphones, or server racks, according to the project. The stated goal is to bring together idle capacity from contributors around the world, while AI customers use the network to access computing power for training their models.
How is RAVEN intended to function within the ecosystem?
The project presents RAVEN as the common medium for transactions inside its proposed compute marketplace. Enterprise customers wanting to rent computing power would pay in RAVEN, while contributors providing that capacity would receive RAVEN as a reward. In this model, the token is described as a mechanism for coordinating payments and incentives between AI-training customers and compute providers.
What is Raven Protocol’s Proof-of-Calculation mechanism?
Raven describes Proof-of-Calculation as the primary basis for regulating and distributing incentives to compute nodes. The mechanism considers how quickly a node performs neural-network gradient calculations and returns them to a Gradient Collector. It also uses redundancy: the project states that only the three fastest redundant calculations qualify for rewards, which is intended to help validate the quality and authenticity of returned gradients.
What role do masternodes have in Raven Protocol’s proposed network?
According to the project, masternodes would help orchestrate the training of different deep neural networks. Raven also states that RAVEN holders could receive rewards for operating these nodes. This gives masternodes a coordinating role distinct from ordinary compute contributors, which are described as supplying processing capacity and being rewarded according to the network’s Proof-of-Calculation incentive rules.
Raven Protocol metric comparison
This comparison is a stored snapshot generated 2026-10-24 06:31 UTC from 262 daily observations available from 2026-02-05 through 2026-10-24. 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
$0.00003097
$0.00005293
$0.00005381
-41.5%
n/a
Market cap
$309.7K
$529.3K
$238.7K
-41.5%
P50.9
YearBull Rank
#7,481
#5,873
#2,693
Lower by 1,608
P11.2
Bull Score
20/100
39/100
54/100
-19.0 pts
P14.3
Turnover
0.01%
0.00%
0.00%
+0.0 pts
P8.5
YB Market Risk
Low
Low
Low
Unchanged
n/a
Cycle
Early
Early
Early
Unchanged
n/a
Median absolute daily movement 1.85%; distance from the highest local daily price -66.1%; circulating supply change +125.4%. These measurements are descriptive and do not predict future direction.
YearBull Rank overview
Latest available YearBull Rank for raven-protocol: #8850.
Rank timeline (last 365 days)
Rank change (daily snapshots).
Reading rule: a smaller rank number indicates stronger placement.
7d window (2026-10-20): #7883 → #8850 (down by 967).
30d window (2026-09-27): #7333 → #8850 (down by 1517).
Stability posture: consistency often matters more than speed.
Market depth: liquidity often shows up as how easily the rank holds its gains.
Venue context: a broader footprint often smooths the rank trajectory.
Trend context: a quick bounce can still be a mean-reversion phase.
Practical note: treat the line as positioning context over time.
YearBull Rank is a comparative index on YearBull that helps contextualize a coin’s position versus others over time. Lower values mean higher placement in the YearBull ordering. Use it as positioning context over time, not as a promise.
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:
Stored venue snapshot. Markets last checked: 2026-07-27. Updated on a rolling basis; no fixed refresh date is promised. Venue listings and volumes are stored snapshots, not live quotes.
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