---
title: "OpenAI API complimentary data-sharing tokens free inference"
description: "A possible free offer exists, but a decisive term still needs verification."
canonical_url: "https://freeinferencing.com/provider/openai_data_sharing_tokens/"
md_url: "https://freeinferencing.com/provider/openai_data_sharing_tokens.md"
last_updated: "2026-09-19"
---

# OpenAI API complimentary data-sharing tokens

> A possible free offer exists, but a decisive term still needs verification.

## Classification

- **Directory:** Watchlist
- **Free access:** Contribution Based
- **Status:** Conditional eligibility
- **Confidence:** High
- **Payment card:** Unknown
- **Account:** Not documented
- **Equivalent paid value:** Not quantifiable


## Models mentioned

- `gpt-5.6-sol`
- `gpt-5.5-2026-04-23`
- `gpt-5.4-2026-03-05`
- `gpt-4.1-2025-04-14`
- `o3-2025-04-16`
- `gpt-5.6-terra`
- `gpt-5.6-luna`
- `gpt-5.4-mini-2026-03-17`
- `gpt-5.4-nano-2026-03-17`
- `gpt-4.1-mini-2025-04-14`
- `o4-mini-2025-04-16`

## Limits and terms

```yaml
reset: 00:00 UTC daily
tiers_1_and_2:
  large_model_group_tokens_per_day: 250000
  small_model_group_tokens_per_day: 2500000
tiers_3_to_5:
  large_model_group_tokens_per_day: 1000000
  small_model_group_tokens_per_day: 10000000
caveat: A request that would cross the quota is billed in full; fine-tuning,
  evals, and tool use are excluded.
```

## What happens to your prompts?

**Partially private.** Privacy protections are incomplete, conditional, or not fully documented.

Privacy is audited separately from price. Review the current governing terms before sending sensitive or regulated data.

## Data governance and agreements

```yaml
data_governance:
  review_status: reviewed
  plan_scope: OpenAI API complimentary data-sharing tokens watchlist offer;
    current free delivery or eligibility remains unresolved.
  prompt_retention: Shared prompts and completions are deliberately provided to
    OpenAI for improvement. Outside the opt-in, default API abuse-monitoring
    logs may contain prompts and responses for up to 30 days, while stateful
    endpoints have separate retention.
  response_retention: Shared outputs receive the same improvement use; Responses
    and other stateful APIs can store application state according to endpoint
    settings, in addition to abuse logs.
  ordinary_logging: Default API abuse-monitoring logs can contain customer content
    and derived metadata for up to 30 days unless a separately approved
    retention control applies.
  model_training: Data sharing is off by default, but this free-token mechanism
    requires an organization owner to opt in to sharing inputs and outputs for
    evaluation and future model training.
  product_improvement: Shared traffic is used to identify usage patterns, measure
    model quality, and inform future evaluation and training.
  human_or_operator_access: Shared traffic enters OpenAI improvement systems.
    Safety exceptions can also permit retention and human review, including for
    certain detected content.
  subprocessors_and_routing: OpenAI processes the selected eligible API traffic;
    data sent through tools such as remote MCP servers is separately governed by
    those third parties.
  deletion_controls: Organization owners can opt out prospectively at any time.
    Opting out ends future sharing but does not promise deletion or model
    unlearning for data already used.
  caveat: Complimentary tokens apply only to eligible organizations and only to
    traffic intentionally shared with OpenAI. A positive account balance is
    required, overages are billed, and Zero Data Retention organizations cannot
    enroll.
```

## Eligibility

```yaml
organization_must_be_selected_by_openai: true
input_output_data_sharing_opt_in_required: true
positive_account_balance_required: true
unavailable_to:
  - Enterprise
  - Zero Data Retention organizations
```

## API compatibility and modalities

- **Compatibility:** Provider-specific or not documented
- **Modalities:** Model inference


## Before you build with OpenAI API complimentary data-sharing tokens

### Read the classification narrowly

This record describes the bounded offer supported by evidence on 2026-09-19; it does not guarantee permanence, production suitability, uptime, latency, model quality, or access from every account and region. “Contribution Based” should be interpreted together with the Watchlist directory placement, High confidence, Unknown payment-card status, and the plan-specific sources below.

### Resolve the live model route

The snapshot records 11 model IDs. Match the exact ID against the provider's current catalog before using it in code because zero-price routes, aliases, context limits, and feature support can rotate while an older documentation page remains online.

### Match the quota to the workload shape

Translate the allowance into peak requests per minute, input and output tokens, concurrency, retries, and every daily or monthly ceiling that applies to the intended account. The first limit reached by the workload is the practical ceiling. A large token pool can still fail interactive bursts, and a high request limit can still fail long-context work. Include tool calls and retry traffic, test the largest realistic payload, and treat research, experimental, and community access as conditional on their eligibility and fair-use terms.

### Preserve billing and privacy boundaries

The recorded payment-card requirement is Unknown, and account access is not documented. Confirm both in the live signup flow, set provider-side budgets when charges are possible, and observe the balance or usage fields after a complete request. The prompt-handling classification is **Partially private** because Privacy protections are incomplete, conditional, or not fully documented. Re-read the terms for the exact route and plan before sending sensitive, regulated, or proprietary content.

### Follow the evidence, then re-check it

This record links 4 first-party sources covering the offer, catalog, limits, pricing, terms, privacy, or adoption evidence available to the audit. Prefer the newest and most specific governing document or live catalog when sources disagree. A dated finding can become stale even when the page remains online, so retain the source and snapshot that supported the decision and submit a correction when a provider changes a material term.

### Plan fallback without policy drift

A fallback should preserve modality, context length, streaming, structured output, tools, safety controls, and data terms, not only API syntax. Decide which errors may retry, cap retry storms, and prevent an exhausted free route from silently switching to a billable model. Rotating aliases and free pools can change behavior without changing the endpoint, so retain the response model field and test at least one substitute route before the primary offer becomes unavailable.

### Monitor the offer as a dependency

Capture the model ID, response model, rate-limit headers, usage fields, latency, HTTP status, and provider request identifier. Watch authorization failure, quota exhaustion, catalog removal, policy revision, and balance movement as separate failure modes. Re-check the live catalog and governing sources on a schedule proportionate to the workload's importance, and keep an owner and exit path for any production dependency on volatile free capacity.

### Test one complete request before scaling

Start with the smallest permitted request using the exact credential, model ID, endpoint, region, and account type intended for deployment. Record the status, headers, usage fields, response model, latency, and dashboard balance movement. Then exercise an invalid model, quota exhaustion, or rate limit so failure is explicit and cannot silently switch to a paid route. Validate streaming, structured output, and tool calls separately because a free model can expose fewer features than its paid counterpart. Keep a budget ceiling outside the application whenever billing is possible, and do not send sensitive data until the observed route matches the reviewed agreement.

## Primary sources

- [Complimentary tokens for shared API traffic](https://help.openai.com/en/articles/10306912-sharing-feedback-evaluation-and-fine-tuning-data-and-api-inputs-and-outputs-with-openai): Official Help
- [API data controls](https://platform.openai.com/docs/models/default-usage-policies-by-endpoint): Official Docs
- [GPT-5.6 Terra](https://developers.openai.com/api/docs/models/gpt-5.6-terra): Official Model Docs
- [Complimentary tokens for shared API traffic](https://help.openai.com/en/articles/10306912-sharing-feedback-and-api-inputs-and-outputs-with-openai): Official Help

## Sitemap

See the full [semantic sitemap](/sitemap.md) for every page and markdown mirror.