Hyprmind is a decentralized AI compute network built on HyperEVM.
GPU miners provide low-cost, verifiable inference; users and intelligent agents pay for compute in USDT; and network revenue is continuously used to buy back $MIND — forming a simple, direct, and economically sustainable loop.
Hyprmind enables open, uncensored, permissionless AI, giving developers, creators, and autonomous agents the ability to run models or build intelligent systems without any centralized control or policy restrictions.
Hyprmind is a distributed GPU network where:
- Miners provide compute, stake $MIND, and earn emissions
- Users pay in USDT for AI inference
- The protocol uses revenue to buy back $MIND
- Builders deploy models, agents, and applications trustlessly
- Inference is verifiable through TEE attestation + proof-of-compute
- Content policies do not exist — builders define their own rules
The network is designed to be a simple, resilient, and permissionless substrate for AI.
A global marketplace of GPU miners grouped into Hardware Clusters, each offering predictable pricing and performance based on the underlying metal.
- Users & applications pay for AI inference in USDT.
- GPU miners earn $MIND emissions for providing compute.
- All network revenue is used to systematically buy back $MIND.
- Miners stake $MIND to join; builders pair with $MIND to launch agents.
- This creates natural token sinks, making $MIND structurally deflationary.
- Low-cost, verifiable inference
- No gatekeepers or censorship
- Hardware-backed economic value
- Permissionless deployment of models, agents, and workloads
Zoomer Quants is not a pillar of the network — it's a stepping-stone project used to validate:
- sovereign agent execution
- TEE-secured signing flows
- multi-process LLM runtime design
- containerized agent behavior
- on-chain metadata evolution
- end-to-end economic loops for autonomous agents
The agents run:
- 13B–20B class LLMs
- deterministic Hyperliquid trading engines
- TEE-secured signature endpoints
- multi-process reasoning + log streaming
- ERC-721 identity with evolving metadata
Zoomer Quants demonstrates the kind of trust-minimized autonomous agents developers will be able to build on Hyprmind.
Centralized AI clouds impose:
- opaque moderation
- unverifiable compute
- inconsistent pricing
- fragile single points of failure
- Heavy biases
Hyprmind provides the opposite:
Anyone can deploy models or agents with any personality or content policy, including fully unrestricted behavior.
Inference is validated using TEE attestation and proof-of-compute mechanisms.
No applications, approvals, or gatekeepers.
Pay in USDT → miners earn $MIND → revenue buys back $MIND.
- DeFi: tamper-proof bots, audit-ready execution logs
- Onchain Agents: autonomous systems that acquire and pay for compute
- DeSci: reproducible scientific workloads (protein folding, large models)
- Oracle Infrastructure: AI summarizing public data into high-integrity feeds
- Unrestricted AI Models: NSFW, edgy, experimental, or alternative personalities
- Agent & Model Launchpad: permissionless business models around intelligent agents
- Minimize trust wherever possible
- Prefer reproducibility over convenience
- Agents should outlive the developers
- Fail loudly instead of silently
- Hardware, not policy, defines the boundary
We welcome contributions in:
- secure enclave engineering (SGX / SEV / TDX)
- distributed inference & p2p compute
- LLM optimization + container execution
- smart contracts (HyperEVM)
- Python agent development
- GPU mining tooling
- node monitoring + telemetry
Open an issue before proposing major changes.
coming soon