---
title: "Entrim.ai free inference"
description: "$10 for new accounts; it does not recur. See verified limits, model IDs, privacy terms, and primary sources for Entrim.ai."
canonical_url: "https://freeinferencing.com/provider/entrim_ai/"
md_url: "https://freeinferencing.com/provider/entrim_ai.md"
last_updated: "2026-09-19"
---

# Entrim.ai

> $10 for new accounts; it does not recur.

## Classification

- **Directory:** Current
- **Free access:** One-time trial
- **Status:** Current trial
- **Confidence:** High
- **Payment card:** Yes
- **Account:** Required
- **Equivalent paid value:** $10.00 once


## Models mentioned

- `authentication_required`
- `GLM 5.3 Flash`
- `Qwen 3.8 27B`
- `DeepSeek V4 Flash`
- `Qwen 3.6 35B-A3B`
- `Gemma 4 26B A4B`
- `Gemma 4 31B`
- `Qwen3 Embedding 8B`
- `GPT OSS 120B`
- `GPT OSS 20B`
- `GLM 5.2`

## Limits and terms

```yaml
signup_credit_usd: 10
recurrence: false
claim_within_days_of_activation: 7
credit_expires_after_days: 14
paid_top_up_stops_expiry: true
effective_for_accounts_activated_at_or_after: 2026-09-02T20:00:00Z
rate_limits: applied_but_not_numerically_published
```

## What happens to your prompts?

**Partially private.** Content records and training are excluded, but derived prompt state may persist in a cross-request cache for up to seven days unless ZDR is requested.

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: Entrim hosted LLM inference API, including the signup-credit trial.
  prompt_retention: Prompts are not written to content logs or stored as records,
    but derived prompt state may persist in memory or limited persistent caches
    for up to seven days; ZDR that disables cross-request caching is available
    on request.
  response_retention: Outputs are not written to content logs or stored as records.
  ordinary_logging: Token counts, timestamps, request IDs, user agent, cost, IP
    address, access, error, security, and billing metadata are retained.
  model_training: Entrim states it does not use customer prompts or outputs to train models.
  product_improvement: Content reuse is excluded; the temporary derived-state
    cache is used for inference performance.
  human_or_operator_access: Terms say Entrim does not monitor or control Customer
    Content, but do not define operator access to transient caches for incident
    response.
  subprocessors_and_routing: Inference runs on Entrim-operated infrastructure in
    Slovenia; Stripe handles payments and ordinary infrastructure/security
    providers process operational data.
  deletion_controls: GDPR access and deletion requests are available through
    Entrim; exact operational-log deletion periods vary by purpose.
  caveat: The default cross-request cache lasts up to seven days unless ZDR is
    approved, so protection depends on account configuration.
agreements:
  terms_of_service: https://entrim.ai/terms-of-service/
  privacy_policy: https://entrim.ai/privacy-policy/
```

## Eligibility

```yaml
account_required: true
email_verification_required: true
one_account_per_person_or_organization: true
payment_card_required_to_claim: true
card_authorization_hold_usd: 1
authorization_hold_released_without_charge: true
```

## API compatibility and modalities

- **Compatibility:** OpenAI Compatible
- **Modalities:** Text Generation, Vision Language, Embeddings, Image / vision


## Before you build with Entrim.ai

### 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, Yes 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 Yes, 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 Content records and training are excluded, but derived prompt state may persist in a cross-request cache for up to seven days unless ZDR is requested. 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

- [Entrim inference API](https://entrim.ai/): Official Product
- [AI model library](https://entrim.ai/ai-models/): Official Catalog
- [Terms of Service](https://entrim.ai/terms-of-service/): Official Terms
- [Privacy Policy](https://entrim.ai/privacy-policy/): Official Privacy

## Sitemap

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