---
title: "WaveSpeedAI free inference"
description: "$1 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for WaveSpeedAI."
canonical_url: "https://freeinferencing.com/provider/wavespeedai/"
md_url: "https://freeinferencing.com/provider/wavespeedai.md"
last_updated: "2026-09-19"
---

# WaveSpeedAI

> $1 for new accounts; it does not recur.

## Classification

- **Directory:** Current
- **Free access:** One-time trial
- **Status:** Current trial
- **Confidence:** High
- **Payment card:** No
- **Account:** Required
- **Equivalent paid value:** $1.00 once


## Models mentioned

No stable model IDs were recorded in this snapshot.

## Limits and terms

```yaml
signup_credit_usd: 1
recurrence: false
expiry: not_published
caveat: Some premium models are unavailable to trial balances; eligible catalog
  entries have positive prices and draw down the credit.
```

## What happens to your prompts?

**Partially private.** A no-training statement exists, but prompt/output TTL, deletion, and third-party model handling remain unresolved.

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: partial
  plan_scope: WaveSpeedAI image, video, and other hosted model APIs and web
    interface; public and third-party models can have separate terms.
  prompt_retention: The terms permit WaveSpeedAI to store and process Customer
    Data as necessary to provide outputs and associated services, but no
    inference-specific maximum retention period is published.
  response_retention: Outputs are Customer Data under the same undefined
    retention; customers are responsible for keeping copies.
  ordinary_logging: Service-performance, use, account, security, and transaction
    information is collected, and aggregated anonymized Resultant Data can be
    retained and used after the service term.
  model_training: WaveSpeedAI's product materials state it does not use customer
    data for training, while the terms reserve service modifications and
    third-party-model rules. No selected-model training matrix was found.
  product_improvement: Aggregated anonymized Resultant Data can be used to improve
    services, development, diagnostics, and corrections; the terms do not
    authorize identifiable content training.
  human_or_operator_access: Content can be processed by WaveSpeedAI and necessary
    service providers for delivery, support, security, and legal compliance; no
    zero-operator-access commitment is published.
  subprocessors_and_routing: Open and third-party models are available and their
    licenses and privacy practices can apply; WaveSpeedAI also uses
    infrastructure, analytics, payment, support, and model-processing providers.
  deletion_controls: not_documented
  caveat: A no-training statement is available, but the public agreements do not
    state a prompt/output TTL or self-service deletion mechanism, so retention
    remains unresolved.
agreements:
  terms_of_service: https://wavespeed.ai/static/terms
  privacy_policy: https://wavespeed.ai/static/privacy
```

## Eligibility

```yaml
account_required: true
payment_method_required: false
```

## API compatibility and modalities

- **Compatibility:** Wavespeed Native Rest
- **Modalities:** Language Models, Image, Video, Audio, Image / vision, Speech / audio


## Before you build with WaveSpeedAI

### 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. “One-time trial” should be interpreted together with the Current directory placement, High confidence, No payment-card status, and the plan-specific sources below.

### Resolve the live model route

No stable model ID is recorded. Resolve the current machine-readable ID, endpoint, authentication method, and request shape from the provider's live documentation before writing fixed production configuration.

### 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 No, and account access is required. 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 A no-training statement exists, but prompt/output TTL, deletion, and third-party model handling remain unresolved. 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 7 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

- [Pricing and signup credit](https://wavespeed.ai/pricing): Official Pricing
- [WaveSpeedAI Terms of Service](https://wavespeed.ai/static/terms): Official Terms
- [WaveSpeedAI Privacy Policy](https://wavespeed.ai/static/privacy): Official Privacy
- [WaveSpeedAI data-use statement](https://wavespeed.ai/landing/introduce): Official Product
- [npm download stats for wavespeed (official WaveSpeedAI JavaScript SDK)](https://www.npmjs.com/package/wavespeed): Package Registry Stats
- [WaveSpeedAI/wavespeed-javascript official SDK repository](https://github.com/WaveSpeedAI/wavespeed-javascript): Official Repository
- [PyPI download stats for wavespeed](https://pypistats.org/packages/wavespeed): Package Registry Stats

## Sitemap

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