τemplar (SN3)
Unlock Schedule
τemplar (SN3) Token Unlock & Vesting Schedule
The unlock chart above provides a clear visual overview of the τemplar (SN3) token release schedule, showing when and how tokens enter circulation across investor, team, treasury, and community allocations. Understanding these tokenomics dynamics is critical for evaluating potential supply pressure, inflation impact, and market liquidity over time — key factors that can influence SN3 price performance.
Each color segment in the chart corresponds to a specific allocation group described in the Allocations section below. Underlying assumptions and data models used to reconstruct this schedule are explained in detail under Assumptions, while broader utility insights and token use cases are covered in Tokenomics & Utility.
Tokenomics & Utility
Where SN3 fits in Bittensor
Bittensor uses a “Dynamic TAO” model in which each subnet has its own alpha (α) token that trades against TAO, the network’s root token. τemplar’s alpha token is SN3. The subnet functions like an automated market maker with two reserves: TAO in reserve and alpha in reserve. The relative price is set by their ratio. When users stake TAO into the subnet, they receive the subnet’s alpha token, which represents participation in that subnet’s economy. (docs.bittensor.com)
Emissions and supply schedule
Bittensor emits TAO and alpha to subnets every block. Alpha emissions begin at 1 α per block (before halving) and follow the same halving cycle as TAO. Alpha produced each block is split between the subnet’s reserve (to deepen liquidity) and “alpha outstanding” held by participants, including miners, validators, and the subnet owner according to on‑chain rules. Bittensor’s docs illustrate a standard maximum supply of 21 million units for each subnet’s alpha. While exact live figures move over time, the schedule and the halving logic are baked into the chain’s design. (docs.bittensor.com)
What SN3 is used for
- Incentives: Validators set weights; emissions pay out to miners and validators according to those weights. Stakers who hold SN3 (having staked TAO for it) share in the subnet’s emissions stream. (docs.bittensor.com)
- Signaling: The amount of TAO staked into a subnet and the resulting price of its alpha token help determine the subnet’s weight in the broader network. That market signal steers emission flows toward productive subnets. (docs.bittensor.com)
- Flexibility: Bittensor now allows subnets to run multiple incentive mechanisms in parallel, each with its own emission split. That means a subnet like τemplar can, in principle, distribute rewards across different evaluation tasks (for example, robustness and data‑quality scoring) while keeping a single token economy. (docs.learnbittensor.org)
Assumptions
- SN3 (a Bittensor subnet token/ALPHA) has uncapped supply.
Official Bittensor tokenomics describe TAO as capped at 21M but describe ALPHA (subnet tokens) as ongoing per-block emissions with up to 14,400 ALPHA/day/subnet; no max supply is stated for ALPHA.
- Genesis date approximated as 2025-06-01.
Earliest confirmed public trading/price data and ATH around June 2025 imply live emissions by that month; exact subnet launch block not stated in public Templar docs.
- Total minted SN3 through 2025-10-25 set equal to reported total supply.
Used CoinGecko’s reported total supply as a proxy for minted SN3 to date due to lack of an official explorer total-supply snapshot; modeled as a single linear unlock from approximate genesis to today for monthly charting.
- Consolidated emissions into one allocation.
Per instructions, network issuance should be represented as a single allocation with notes describing sub-components (participants vs pool). Split between the two sub-components is dynamic and not precisely published per subnet, so we did not fabricate a breakdown.
Allocations
Description
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Templar is a decentralized training framework for large language models on Bittensor, using global computational nodes to collaboratively train models, reward contributions fairly, and compress network traffic for efficient large-scale AI training.
| Sector: | AI & Compute |
| Blockchain: | Bittensor |