Skip to main content

Mainframe (Macrocosmos AI)

Mainframe (Macrocosmos AI) — a reference card for a crypto project: what the product does and how verifiable the project’s key claims are; also — alignment with the Decentralized AI thesis (DecAI Fit).

Mainframe (Macrocosmos AI) — an AI/Compute | Infra project on the Bittensor network (Subnet 25).

Disclaimer

Important: this page is a reference overview of the project. Within DecAIHub, we separately record a verification based on open sources within the AI thesis (what is real AI/onchain/why a token, and which sources this is based on).
This is not financial advice and not a recommendation to buy/sell/hold any asset. We do not assess price, returns, or entry/exit timing.
Conclusions are based on publicly available materials found as of the verification date. The absence of confirmation does not imply the absence of the technology.

TL;DR (for readers who are not into AI)

  • What it is: a “science compute” subnet on Bittensor for tasks from drug discovery/bioinformatics (including protein folding / docking).
  • Who it’s for: researchers/companies, as well as the subnet’s miners/validators.
  • Why onchain/token: the Bittensor onchain layer is used for incentives/accounting of contributions and emission distribution.
  • What you can actually touch (Tier‑1): the subnet’s public code + app and dashboard.

How it works (very briefly)

  1. The user/system forms a job: a simulation/docking task.
  2. Miners compute: perform the computations (for example, OpenMM simulations) and publish the results.
  3. Validators verify: evaluate quality/metrics and form weights/rewards.
  4. Where the blockchain is: accounting of contributions and incentives/emissions go through the Bittensor subnet mechanics.
  5. Token role: incentives and distribution of rewards to subnet participants.

Quick links: AI thesis fit

Project passport

Field Value
Project name Mainframe (Macrocosmos AI)
Also known as (aliases) Subnet 25 Mainframe, SN25; Protein-Folding (legacy name)
Logo (logo) ../assets/456_mainframe-macrocosmos-ai_logo.jpg
Token symbol (ticker) —
Category AI/Compute | Infra
Primary chain (chain) Bittensor
Type Appchain
Network status mainnet
Consensus (consensus) —
Launch date (launch_date) 2024-06
Project status (status) active
Token (standard) —
Token contract —
Token model (token_type) —
Max supply —
Issuance —
Tokenomics (tokenomics, brief) Rewards/emissions are distributed to the subnet’s miners and validators via the Bittensor mechanics.
Governance —
Admins/keys —
Audit —
Bug bounty —
Team (team) Macrocosmos AI
Funding (investors/funding) —
AI component (ai_component) protein folding compute (MD + docking)
Use‑case (use_case) protein folding jobs + docking compute
DecAI Fit — AI thesis fit 2/6 — low alignment with the Decentralized AI thesis
DecAI Fit component summary ai_score 2 / onchain_score 2 / token_score 0 / evidence_score 0
Last verified 2026-02-11

General project overview

Mainframe is a Bittensor subnet focused on computational tasks from life sciences and drug discovery. In Tier‑1 sources, the project is described as a “decentralised science subnet”, where miners perform scientific computations (for example, molecular dynamics via OpenMM), and validators measure the contribution and distribute rewards within the subnet’s incentive architecture.

Features/modules

  • Bittensor subnet (SN25): miners perform computations, validators evaluate the results and form weights/payouts.
  • Task pipeline: Tier‑1 sources single out protein folding (MD) and docking (DiffDock is mentioned, among others).
  • App and dashboard: interfaces for interaction and for observing subnet metrics.

Typical scenarios

  • Scenario 1: a researcher/company uses the subnet as a compute layer → receives simulation/computation results.
  • Scenario 2: an operator runs a miner → computes jobs and receives rewards based on the subnet’s metrics/weights.
  • Scenario 3: a validator verifies miners’ results → influences the distribution of incentives.

Getting started (wallet/network)

  • What you need: an environment for running a miner/validator and compute resources (see the Tier‑1 documentation).
  • Network/chain: Bittensor (Subnet 25).
  • Fees: participation costs depend on the network and infrastructure; details — in Tier‑1 sources.

Architecture/tech (non‑AI)

  • Components: the subnet’s miners/validators, subnet services, task storage/pipelines, app/dashboard.
  • Participant roles: users/task requesters, miners, validators, supporting services.
  • Where logic runs: computations — offchain at the miners; accounting of contributions/incentives — via the Bittensor onchain layer.
  • Dependencies: computational libraries/tools (OpenMM is mentioned in Tier‑1) and the network infrastructure.

Token/economics (expanded, no forecasts)

  • Token utility: rewarding miners/validators for computations and quality verification.
  • Protocol necessity drivers: incentives are needed to attract compute resources and to maintain the verifiability of results.
  • Who pays fees: — (not established per Tier‑1).
  • Where fees go: — (not established per Tier‑1).
  • Issuance/burn: — (not established per Tier‑1).
  • Security/incentive mechanisms: validation of results and distribution of weight/rewards.
  • Distribution and token issuance schedule: — (not established per Tier‑1).
  • Treasury: —.

Governance

  • Who makes decisions: — (not established per Tier‑1).
  • How protocol parameters change: —.
  • Where decisions are discussed/made: GitHub (issues/PR) and public updates (see links_*).
  • Keys/multisig: —.

Security and incidents

  • Audits: — (not established per Tier‑1).
  • Bug bounty: — (not established per Tier‑1).
  • Incidents: — (not established per Tier‑1).
  • Threat model: the risks are related to the quality of validation and potential attempts to manipulate metrics/computations.

Project status and timeline

  • Current status: active.
  • Key releases/milestones: the launch is listed as June 2024 (see the Tier‑1 docs).
  • Roadmap: updates are published in the Substack tag (see links_*) and in GitHub releases.

Ecosystem/integrations

  • Integrations: —.
  • Partners: the Tier‑1 README claims a partnership with Rowan Scientific (as context; not used for DecAI Fit).
  • Where it’s actually used: the subnet’s app and dashboard (see links_*).

AI component of the project

  • What is real AI here? Tier‑1 sources describe tasks that are often associated with AI/ML in drug discovery (for example, docking using DiffDock), but the main layer is distributed computing/simulations.
  • What is truly onchain? accounting and incentivization of participants within Bittensor Subnet 25.
  • Why is a token needed? incentives/distribution of rewards to miners and validators for computations and validation.
  • Red flags (based on the information found): claims about “AI quality” without reproducible metrics; unclarified subnet tokenomics parameters without Tier‑1 specifications.

DecAI Fit component summary

  • DecAI Fit: 2/6 — low alignment with the Decentralized AI thesis
Component Level Score
AI reality medium 2
Onchain necessity medium 2
Token necessity low 0
Evidence Tier‑1 present 0
Details

AI reality

AI_0 — AI intent (Tier‑1 roadmap) (1/0)

  • AI_0 (decision): 0
  • Claim (one line): Tier‑1 sources describe the subnet’s specific computational tasks/pipelines, not just “AI intent”.
  • Evidence: Tier‑1 — https://github.com/macrocosm-os/mainframe
  • Why sufficient / why not (one line): AI_0 applies when there is only intent; here there is a description of the tasks and the implementation.
  • Conflict note (if any): —

AI_1 — what the AI does (1/0)

  • AI_1 (decision): 1
  • Claim (one line): The subnet performs computations for life sciences tasks: MD simulations (OpenMM) and docking (DiffDock is mentioned).
  • Evidence: Tier‑1 — https://github.com/macrocosm-os/mainframe ; https://docs.macrocosmos.ai/subnets/subnet-25-mainframe
  • Why sufficient / why not (one line): Tier‑1 sources describe the purpose of the subnet and the types of computations related to the ML/AI context of drug discovery.
  • Conflict note (if any): —

AI_2 — demos/examples (1/0)

  • AI_2 (decision): 1
  • Claim (one line): There is a subnet app and dashboard for observing state/metrics and for interaction.
  • Evidence: Tier‑1 — https://app.macrocosmos.ai/mainframe ; https://www.macrocosmos.ai/sn25/dashboard
  • Why sufficient / why not (one line): The presence of the app/dashboard provides a reproducible “surface” of the product.
  • Conflict note (if any): —

AI_3 — metrics/quality (1/0)

  • AI_3 (decision): 0
  • Metrics: —
  • Context (version/date/how measured): —
  • Evidence: Tier‑1 — https://github.com/macrocosm-os/mainframe
  • Why sufficient / why not (one line): No unified set of quality metrics for the AI component (for example, model accuracy/benchmarks) is singled out under the AI_3 rules (not identified per Tier‑1).
  • Conflict note (if any): —

AI_4 — tech description/architecture/versions (1/0)

  • AI_4 (decision): 0
  • Claim (one line): There is a tech description of the subnet and the computational tasks, but no tech description of a specific AI model/versions as a key artifact was found.
  • Evidence: Tier‑1 — https://docs.macrocosmos.ai/subnets/subnet-25-mainframe
  • Why sufficient / why not (one line): AI_4 requires a tech description of the AI model/versions; here the focus is on the computational pipeline.
  • Conflict note (if any): —

Onchain necessity

OC_1 — contracts/addresses/chain (1/0)

  • OC_1 (decision): 1
  • Chain: Bittensor (Subnet 25)
  • Addresses/identifiers: Subnet 25 (SN25)
  • Evidence: Tier‑1 — https://docs.macrocosmos.ai/subnets/subnet-25-mainframe ; https://github.com/macrocosm-os/mainframe
  • Why sufficient / why not (one line): Tier‑1 sources directly identify the subnet and its role in Bittensor.
  • Conflict note (if any): —

OC_2 — onchain beyond just a token (1/0)

  • OC_2 (decision): 1
  • What useful logic is onchain: accounting of contributions/weights and distribution of incentives/emissions between miners and validators.
  • Evidence: Tier‑1 — https://github.com/macrocosm-os/mainframe
  • Why sufficient / why not (one line): The Tier‑1 README describes the subnet’s incentive architecture and reward distribution.
  • Conflict note (if any): —

OC_3 — onchain is critical (1/0)

  • OC_3 (decision): 0
  • “Replace the blockchain” test: no Tier‑1 justification was found that without the blockchain the product “breaks down” (rather than turning into a centralized compute marketplace).
  • Evidence: Tier‑1 — https://docs.macrocosmos.ai/subnets/subnet-25-mainframe
  • Why sufficient / why not (one line): OC_3 requires an explicit argument “which key property is lost”; not recorded per Tier‑1.
  • Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

  • TK_0 (decision): 0
  • Claim (one line): The subnet’s token incentives are implied in the Bittensor logic, but the exact ticker/standard for the project is not established per Tier‑1.
  • Evidence: Tier‑1 — https://github.com/macrocosm-os/mainframe
  • Why sufficient / why not (one line): One cannot assert “no token”; but there is also no exact Tier‑1 ticker/standard.
  • Conflict note (if any): —

TK_1..TK_4 (1/0)

TK_1 — payment for the service (1/0)

  • TK_1 (decision): 0
  • Claim (one line): No Tier‑1 description of a pay‑per‑job/purchase mechanic with the token for users as a mandatory element was found.
  • Evidence: Tier‑1 — https://docs.macrocosmos.ai/subnets/subnet-25-mainframe
  • Why sufficient / why not (one line): A “payment for the service” model with the token is not recorded per Tier‑1.
  • Conflict note (if any): —

TK_2 — incentives/collateral/penalties (1/0)

  • TK_2 (decision): 0
  • Claim (one line): Incentives are described at the subnet level, but the specific conditions of collateral/penalties are not established per Tier‑1.
  • Evidence: Tier‑1 — https://github.com/macrocosm-os/mainframe
  • Why sufficient / why not (one line): TK_2=1 requires specific staking/slashing parameters.
  • Conflict note (if any): —

TK_3 — governance (1/0)

  • TK_3 (decision): 0
  • Claim (one line): Governance use of the token is not established per Tier‑1.
  • Evidence: Tier‑1 — https://docs.macrocosmos.ai/subnets/subnet-25-mainframe
  • Why sufficient / why not (one line): There is no explicit description of voting/governance via the token.
  • Conflict note (if any): —

TK_4 — token is replaceable (1/0)

  • TK_4 (decision): 0
  • Claim (one line): The replaceability of the token/incentives with another mechanism is not established per Tier‑1.
  • Evidence: Tier‑1 — https://docs.macrocosmos.ai/subnets/subnet-25-mainframe
  • Why sufficient / why not (one line): TK_4 requires an explicit argument; not identified per Tier‑1.
  • Conflict note (if any): —

Evidence (table)

Tier Source What it proves
Tier‑1 https://docs.macrocosmos.ai/subnets/subnet-25-mainframe The purpose of Subnet 25, a description of the tasks (MD/protein folding) and the launch context (June 2024).
Tier‑1 https://github.com/macrocosm-os/mainframe Description of the subnet/tasks, the incentive architecture, links to the app/dashboard.
Tier‑1 https://app.macrocosmos.ai/mainframe App (product surface).
Tier‑1 https://www.macrocosmos.ai/sn25/dashboard Subnet dashboard (metrics/observation).
Tier‑2 https://taostats.io/subnets/25/chart Subnet visualization/metrics (context).
Tier‑1 — No Tier‑1 source for claim “exact ticker/standard of the project token” was found / not confirmed by Tier‑1.

No comments to display

Back to top