Give every expert model a market.

Give every expert model a market.

Researchers, labs, and fine-tuners can bring local and open-weight models to market and earn from every inference.

Researchers, labs, and fine-tuners can bring local and open-weight models to market and earn from every inference.

Completed work

Delivered results

Index observation

Rewarded providers

  • Matching

  • Routing

  • VERIFICATION

  • INCENTIVES

  • SETELMENT

COORDINATION LAYER

Requests

Capital

Data

Compute

Tools

Completed work

Delivered results

Index observation

Rewarded providers

  • Matching

  • Routing

  • VERIFICATION

  • INCENTIVES

  • SETELMENT

COORDINATION LAYER

Requests

Capital

Data

Compute

Tools

Completed work

Delivered results

Index observation

Rewarded providers

  • Matching

  • Routing

  • VERIFICATION

  • INCENTIVES

  • SETELMENT

COORDINATION LAYER

Requests

Capital

Data

Compute

Tools

Providers observed in the index

Open participation

Open participation

Specialized models deserve a path to market.

npi · 24h

volume-weighted, never estimated

For creators

Turn local models into market-ready services.

Fine-tune an open-weight model, serve it on your own infrastructure or through a compute provider, and earn whenever users call it.

settled job

index

  • job 4a12

    ✓

  • job 4a13

    ✕

  • job 4a14

    ✕

For users

Access expertise per request.

Discover expert models built for fields like biomedicine, law, finance, and science. Pay for the inference you need without owning infrastructure.

frame n

0x9f3c…

✓

fold offline · compare head

For providers

Earn from real model usage.

Serve your own model or work with a compute provider. Each finalized request pays the provider, funds the protocol, and can unlock additional incentives.

Market flow

Market flow

From expert model
to paid inference.

Creators publish specialized models. Users bring demand. Providers execute requests, and finalized work produces revenue, incentives, and a transparent market record.

Creator revenue

volume-weighted, never estimated

Model reputation

Ollama-3-70-B

75%

gemma 70-2-B

52%

Mistral02-9B

12%

Provider record

by executing provider

Job + escrow

model, onchain payment locked

Execution

compute provider bonds & runs

Delivery + evidence

result hash, signed frame (SJP-1)

Challenge window

fraud check — Type A or B

Finalization

only settled jobs become observations

User

buyer posts escrow

Developer

application · api call

AI agent

autonomous dispatch

Creator revenue

volume-weighted, never estimated

Model reputation

Ollama-3-70-B

75%

gemma 70-2-B

52%

Mistral02-9B

12%

Provider record

by executing provider

Job + escrow

model, onchain payment locked

Execution

compute provider bonds & runs

Delivery + evidence

result hash, signed frame (SJP-1)

Challenge window

fraud check — Type A or B

Finalization

only settled jobs become observations

User

buyer posts escrow

Developer

application · api call

AI agent

autonomous dispatch

Settlement gate

All contract conditions must pass before providers are paid and activity becomes reputation.

Hash-chained transcripts

Every lifecycle transition is a signed SJP-1 frame — replayable by any third party.

Creator economics

Finalized usage pays providers and can add protocol incentives without changing the buyer quote.

How it works

From personalized & local model to paid inference.

Each step maps to a contract call. The SJP-1 transcript records every transition as a signed, hash-chained frame replayable offline by any third party.

01

01

Build locally and publish globally

Start with a local or open-weight model, fine-tune it for a specific domain or workflow, then register it on OpenAlmond. Serve it directly or connect a compute provider.

01

Build locally and publish globally

Start with a local or open-weight model, fine-tune it for a specific domain or workflow, then register it on OpenAlmond. Serve it directly or connect a compute provider.

02

02

User requests inference

A user, application, or agent selects the model, defines the request, and posts the quoted onchain payment in escrow. The buyer knows the price before execution begins.

02

User requests inference

A user, application, or agent selects the model, defines the request, and posts the quoted onchain payment in escrow. The buyer knows the price before execution begins.

03

03

Provider accepts and executes

An admitted provider reserves capacity, bonds the job, and runs the requested model. The model creator may serve directly or rely on another compute provider.

03

Provider accepts and executes

An admitted provider reserves capacity, bonds the job, and runs the requested model. The model creator may serve directly or rely on another compute provider.

04

04

Delivery becomes verifiable

The provider returns the result with signed, hash-chained evidence. A challenge window lets the protocol reject invalid delivery or self-dealing before payment becomes final.

04

Delivery becomes verifiable

The provider returns the result with signed, hash-chained evidence. A challenge window lets the protocol reject invalid delivery or self-dealing before payment becomes final.

05

05

Creator and provider earn

When the job finalizes, the provider receives the buyer payment minus the explicit protocol fee. Eligible providers can receive additional protocol incentives from a separate, pre-funded ledger.

05

Creator and provider earn

When the job finalizes, the provider receives the buyer payment minus the explicit protocol fee. Eligible providers can receive additional protocol incentives from a separate, pre-funded ledger.

Market outcomes

A market that rewards real expertise.

Specialized models reach global demand. Creators and compute providers earn from usage. Finalized settlements keep the resulting market history transparent.

Earnings

Usage

Jobs

EXECUTION

Model creators

Publish specialized models. Eevry call pays them.

Demand Side

Global demand

Users worldwide pay per inference, in one market.

EXECUTION

Compute providers

Run jobs, prove delivery, earn on settlement.

Payments

Earnings

Usage

Jobs

EXECUTION

Model creators

Publish specialized models. Eevry call pays them.

Demand Side

Global demand

Users worldwide pay per inference, in one market.

EXECUTION

Compute providers

Run jobs, prove delivery, earn on settlement.

Payments

Settlement intelligence

Transparent pricing from real paid work

Every finalized job leaves a public price record: what was paid, how much work was delivered, and which model and provider served it. Pricing on OpenAlmond comes from real paid work.

Specialized supply

Expert models become accessible services

Researchers, labs, fine-tuners, and teams can turn local and open-weight models into paid services built for specific domains.

Flexible serving

Serve directly or delegate compute

Compute providers are admitted, bonded participants who accept and deliver jobs. Provider-level views show the distribution of settled prices across a participant’s history. They describe realized settlement activity, not capability claims.

Open demand

Users pay per inference

Users, applications, and agents can request specialized intelligence through a shared market and pay only for the work they ask the network to execute.

Creator economics

Real usage creates revenue

Each finalized request pays the serving provider. Protocol incentives can add a separate reward on top, giving specialized models a path from research artifact to recurring service.

Fee transparency

Payment and fees stay explicit

The buyer sees the quoted payment before execution. The protocol fee is explicit, and gross versus net settlement records keep its effect visible without rewriting the buyer price.

Market history

Real work builds market reputation

Finalized jobs create a transparent price index and verifiable records of volume, models, and providers. Empty markets stay empty.

FAQs

Questions
the index answers.

Questions
the index answers.

What is OpenAlmond?

Who can publish a model?

Can I monetize a local or open-weight model?

How are models served?

How do users pay for inference?

How do model creators and providers earn?

Why is settlement onchain?

What role does the price index play?

How do I verify a transcript?

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