grail (SN81)

Overview

grail (SN81) market snapshot: Price $1.2300, market capitalization $5.89M, and reported 24-hour volume $150.25K.

Trading activity: Reported 24-hour volume equals 2.55% of market capitalization. The local markets snapshot lists Subnet Tokens among venues with observed trading activity.

YearBull indicators: YearBull Rank #8,468. Bull Score 22/100. YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment. Cycle Early. Observed price change: 24h -1.60% · 7d -11.51% · 30d -36.27%.

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 grail (SN81)?

YearBull Project Summary: This editorial evidence review sets out the documented purpose, mechanism and token context for grail. It separates confirmed source material from information that requires current independent verification, including market data, supply figures, contract state and operational availability.

Source description

“Grail operates as subnet 81 on the Bittensor network, serving as the reinforcement learning fine-tuning and post-training layer of the Covenant AI ecosystem. The project implements the GRAIL protocol (Guaranteed Rollout Authenticity via Inference Ledger) to provide cryptographically verifiable model outputs during reinforcement learning rollouts. Grail transforms foundation models from pre-training subnets into deployable, aligned AI systems through permissionless, incentivized RL fine-tuning infrastructure. The platform generates thousands of rollouts per second using custom algorithms designed for post-training optimization. The subnet supports models ranging from 8B to 70B+ parameters and integrates with multiple RL environments for diverse training scenarios.”

This source-supplied description may contain old, promotional, or unverified claims and is not YearBull editorial analysis.

grail (SN81) project facts

Official links and contract records appear in Key Facts. Project details can change, so verify current information with the project.

grail (SN81) FAQ

What is Grail (SN81) within the Bittensor network?

Grail operates as subnet 81 on Bittensor and is described as the reinforcement learning fine-tuning and post-training layer of the Covenant AI ecosystem. Its stated role is to help transform foundation models produced by pre-training subnets into deployable, aligned AI systems through permissionless and incentivized reinforcement learning infrastructure.

What is the GRAIL protocol designed to do?

The GRAIL protocol—short for Guaranteed Rollout Authenticity via Inference Ledger—is described as a system for providing cryptographically verifiable model outputs during reinforcement learning rollouts. In practical terms, the project presents it as a way to support the authenticity and verification of outputs generated while models are being fine-tuned through reinforcement learning.

How does Grail approach reinforcement learning fine-tuning?

Grail describes its platform as permissionless, incentivized infrastructure for reinforcement learning fine-tuning and post-training optimization. The project states that it uses custom algorithms to generate thousands of rollouts per second, with the goal of improving foundation models after their initial pre-training and preparing them for deployment in aligned AI systems.

How does Grail relate to the Covenant AI ecosystem?

Grail is described as the reinforcement learning fine-tuning and post-training layer of the Covenant AI ecosystem. Within that stated structure, pre-training subnets provide foundation models, while Grail focuses on subsequent reinforcement learning and alignment work intended to turn those models into deployable systems.

grail metric comparison

This comparison is a stored snapshot generated 2026-10-22 06:31 UTC from 292 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.

MetricSnapshot30d before90d beforeChange vs 30dUniverse percentile
Price$1.34$1.90$1.70-29.5%n/a
Market cap$6.37M$8.81M$7.05M-27.6%P82.0
YearBull Rank#6,855#632#1,859Lower by 6,223P19.6
Bull Score27/10062/10052/100-35.0 ptsP19.6
Turnover1.19%29.78%1.35%-28.6 ptsP58.7
YB Market RiskLowLowLowUnchangedn/a
CycleEarlyEarlyEarlyUnchangedn/a

Median absolute daily movement 3.23%; distance from the highest local daily price -85.1%; circulating supply change +61.2%. These measurements are descriptive and do not predict future direction.

Editorial research. Identity, project facts, sources, and risks below belong to the dated editorial review. The live analytical snapshot above may be newer and is generated separately from stored market data.

grail (SN81): project purpose, mechanism and token context

This editorial evidence review sets out the documented purpose, mechanism and token context for grail. It separates confirmed source material from information that requires current independent verification, including market data, supply figures, contract state and operational availability.

grail is described in the reviewed source record as follows: The official grail repository describes grail as a Bittensor subnet implementation for verifiable post-training of language models, while GRAIL is the protocol for tying rollouts to model and input identity. This establishes the documented project purpose, but it is not a statement about price, adoption, reserves or future performance.

The documented operating model adds this context: The repository says miners generate rollouts, validators verify proofs and evaluate environments, and a trainer runs reinforcement learning on validated rollouts before publishing checkpoints. Readers should separate that stated mechanism from any interface, contract or market condition visible today. Product rules and integrations can change.

The evidence set also records: The implementation is identified as Bittensor Subnet 81, with the subnet reference and market profile using netuid 81 and symbol SN81. This helps explain the role of grail within its network or product, while leaving any unsupported reward, liquidity or performance claim unresolved.

Identity is important because similar names, wrapped assets and historical deployments can coexist. The reviewed record states: The official technical description lists cryptographic commitments, verifier-supplied challenges, model binding and environment-specific evaluation as parts of the GRAIL verification flow. Before interacting with grail, verify the active chain, contract and official interface rather than relying on a ticker alone.

For token role and disclosed design, the source material says: The official repository states that the current default environment is Triton Kernel and documents other supported or available environments such as 3-SAT, GSM8K, MATH, MBPP and HumanEval. Where supply, allocation, emissions, vesting or burn details are absent, this profile leaves them unresolved and does not infer a current figure.

The cited record adds: The secondary subnet overview describes distributed training through miners and validators and identifies the former Patrol naming as part of the project's history; this historical rebrand is not used to infer ownership or future performance. This is useful technical background, but it does not replace operational due diligence. Permissions, counterparties, oracles, bridges and withdrawal conditions can affect real use.

One additional evidence-bound observation is: CoinGecko provides live SN81 market fields and classifies grail in the Bittensor and AI categories; price, volume, supply and rank are time-sensitive and excluded from permanent claims. The editorial conclusion is limited to the cited record and deliberately avoids price targets, return projections and claims that a mechanism will deliver a particular outcome.

When assessing current status, the key question is what has been independently confirmed at the time of use. The dossier supports this point: The official grail repository describes grail as a Bittensor subnet implementation for verifiable post-training of language models, while GRAIL is the protocol for tying rollouts to model and input identity. Later official records take precedence if contracts, terms or deployments change.

The project documentation provides a basis for describing intended scope, not for filling every data gap. The reviewed material says: The repository says miners generate rollouts, validators verify proofs and evaluate environments, and a trainer runs reinforcement learning on validated rollouts before publishing checkpoints. Current market metrics and operational availability require separate, dated verification.

Finally, the evidence record notes: The implementation is identified as Bittensor Subnet 81, with the subnet reference and market profile using netuid 81 and symbol SN81. The practical takeaway is to verify identity, chain, contract details and current risk disclosures before acting. This is especially important where custody, lending, bridges or external dependencies are involved.

YearBull Rank overview

Most recent YearBull Rank reading for patrol-tao-com is #8468.

Rank timeline (last 365 days)

Rank change (reference points).

Reading rule: a smaller rank number indicates stronger placement.

  • 7d window (2026-10-21): #6325 → #8468 (down by 2143).
  • 30d window (2026-09-28): #7069 → #8468 (down by 1399).

YearBull Rank is a relative placement score used on YearBull to compare a coin against peers within the same dataset. Lower rank numbers correspond to stronger relative placement.

Risk angle: short bursts do not always translate into durable placement. If the last week is quiet, the current rank is usually easier to trust.

Liquidity posture: stable placement often correlates with stable participation. If the curve improves but won’t hold, treat it as flow-driven.

Cycle placement: phase changes usually leave a footprint in consistency. If both are flat, the coin may be tracking its peer basket.

Market structure: fragmentation can make rank more reactive. If rank can’t hold gains, it can be concentrated pressure.

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
Research context

Related research and comparable assets

All hubs →

Similar coins

Popular by YearBull Rank

grail (SN81) Markets

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.
Exchange Top Pair Stored 24h volume (snapshot) Trust Rank
Subnet Tokens SN81/SN0 $120.34K #200

Listings are ordered by reported snapshot volume. Trust Rank is an external venue-quality indicator; it is not an endorsement or a solvency guarantee.