How to Share Unused AI Model Capacity and Earn Credits Responsibly

If a local model, private deployment, or model API is idle for much of the day, you may want to make the capacity you are allowed to share available to other callers. Fasten Share lets a producer publish a backend as an online node. After successful consumer calls, the platform records producer credits based on actual forwarded usage.

The most important question is not whether an endpoint can be connected. It is whether you have the right to use, forward, and share that model capacity. Subscription, account, API, and cloud-service terms differ. Permission to use a model yourself does not automatically include resale or third-party access.

Decide what you are allowed to share

Appropriate capacity may include:

• Ollama, LM Studio, vLLM, or another inference service that you operate and may expose;
• a private model API your team or organization has explicitly authorized for sharing;
• a third-party API whose terms allow proxying, forwarding, or commercial use;
• a backend you can maintain and whose usage cost and availability you are willing to manage.

Do not infer permission from technical access. Before configuring a producer node, review the upstream account terms, subscription restrictions, forwarding policy, regional rules, and commercial-use requirements. If the answer remains unclear, prefer a self-hosted model or an endpoint with explicit authorization.

Prepare a stable backend first

The node experience depends on the real backend, not merely on Fasten Share displaying “online.” Test the backend directly from the machine that will run the producer client:

1. The base URL is reachable from that runtime environment.
2. The protocol, version prefix, and model name match the backend.
3. The API key is valid and does not have unnecessary administrative privileges.
4. Both regular and streaming responses work when you need them.
5. The machine will not sleep unexpectedly, and the network and upstream quota can handle your planned concurrency.

When the backend runs on the same machine, a desktop client can often use 127.0.0.1 or localhost. If the Fasten Share client runs in Docker, 127.0.0.1 points to the container itself, so use an address that can reach the host or a service on the same Docker network.

Add the backend in Fasten Share

Install the client from the official download page, sign in, and add a backend on the producer page. Verify each field carefully:

Field	Purpose	Common mistake
Base URL	Host address for the model service	Including /v1 here and again in the version prefix
Protocol	Determines request shape and health checks	Selecting OpenAI for an Anthropic endpoint
Models	Real identifiers exposed for discovery	Using a display label instead of the backend model ID
API key	Credential used locally to call the backend	Entering a consumer key or copying surrounding whitespace
Max concurrency	Limit on simultaneous producer requests	Setting it above the backend or account capacity
Credit multiplier	Metering multiplier for consumers	Starting too high before validating demand and stability

Save the configuration, start sharing, and wait until the client reports a connected, registered, healthy node. If the health check fails, verify the backend directly before changing Fasten Share fields.

How the upstream key is protected

The upstream API key stays on the producer device. A consumer calls Fasten Share with a separate consumer API key. Only after the request reaches the producer client does the local client inject the upstream credential into its call to the model backend.

Consumers do not receive the original key, and the Fasten Share service does not need to store it. However, consumer requests and model responses still pass through the Fasten Share service for routing, metering, and settlement. Credential separation is not end-to-end encryption and should not be presented as if the platform cannot see business traffic.

Create a dedicated, least-privilege upstream key for sharing when possible. Configure upstream budgets, concurrency limits, or quota alerts. Stop the backend and rotate the key immediately if you suspect exposure or unexpected usage.

Understand producer credits and withdrawals

Successful consumer usage is recorded as producer credits. Consumer credits used for inference and producer credits earned through sharing are separate balances.

Conversion rates, withdrawal thresholds, review steps, and payout methods may change with operating and compliance requirements. This evergreen guide deliberately avoids hard-coding values that may become stale. The rules shown in the client when you apply are authoritative.

Publishing a node also does not guarantee usage. Demand depends on the model, protocol, availability, ratings, multiplier, concurrency, and consumer choice. Fasten Share does not promise a fixed request volume or income.

Improve long-term availability

• Start with conservative concurrency and increase it only after observing latency and errors.
• Publish exact model identifiers and keep the first health-check model available.
• Prevent sleep, unstable network changes, and accidental proxy reconfiguration.
• Choose a multiplier that consumers can understand and evaluate.
• Monitor upstream quota, rate limits, expiration, and service incidents.
• Take an unhealthy backend offline while diagnosing it instead of accumulating failed calls.

Pre-launch checklist

• Sharing and forwarding rights are confirmed.
• A direct request to the backend succeeds.
• The base URL does not duplicate the version prefix.
• Model IDs, protocol, and credential match the backend.
• A dedicated least-privilege key and upstream alerts are in place.
• Maximum concurrency stays within hardware and account limits.
• You understand that inference traffic passes through Fasten Share.
• You understand that producer credits are not guaranteed cash income.

When ready, use the quick start to learn the interface. Then follow the Ollama guide for a local model or the compatible API guide for an online or private endpoint.