---
title: "Logfare free inference"
description: "A recurring no-cost API allowance covering 23 cataloged models."
canonical_url: "https://freeinferencing.com/provider/logfare/"
md_url: "https://freeinferencing.com/provider/logfare.md"
last_updated: "2026-09-19"
---

# Logfare

> A recurring no-cost API allowance covering 23 cataloged models.

## Classification

- **Directory:** Current
- **Free access:** Always-free quota
- **Status:** Community service
- **Confidence:** High
- **Payment card:** No
- **Account:** Required
- **Equivalent paid value:** Not quantifiable
- **API endpoint:** `https://logfare.ai/v1`

## Models mentioned

- `sdxl-lightning`
- `flux-2-klein-4b`
- `flux-2-klein-9b`
- `flux-2-dev`
- `flux-1-schnell`
- `logfare/auto`
- `mimo-v2.5`
- `gemma-4-26b`
- `whisper-large-v3-turbo`
- `deepseek-v3.2`
- `moondream3.1`
- `kimi-k2.5`
- `glm-5`
- `grok-4.6`
- `phoenix-1.0`
- `melotts`
- `kimi-k2.6`
- `deepseek-v4-flash-0731`
- `aura-2-en`
- `qwen-3.8-max`
- `nova-3`
- `lucid-origin`
- `qwen-3.8-27b`

## Limits and terms

```yaml
numeric_limit: none_published
policy: fair_use
caveat: Excessive or automated traffic may be throttled or blocked.
```

## What happens to your prompts?

**Not private.** Every request body is logged and scrubbed content may be used in internal evaluation datasets; premium access can require training opt-in.

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: Logfare standard and premium free API routes under policy version 3.1.
  prompt_retention: Every request body is logged after best-effort PII scrubbing.
    The privacy policy defines retention by store and warns that scrubbing is
    imperfect.
  response_retention: Every response body is logged after the same best-effort
    scrub and can enter internal evaluation datasets.
  ordinary_logging: IP addresses, forwarded-for values, User-Agent, headers,
    timestamps, token counts, model, prompts, responses, and metadata are
    collected; network/client identifiers are retained up to 90 days.
  model_training: Standard-tier content is not used for training by default.
    Premium access requires voluntary, reversible opt-in; already incorporated
    training data cannot be removed from a trained model.
  product_improvement: Post-scrub content may be used in private internal
    evaluation and benchmarking datasets on a legitimate-interest basis,
    including standard-tier requests.
  human_or_operator_access: Authorized Logfare personnel can access protected
    internal datasets; upstream providers receive request content to perform
    inference.
  subprocessors_and_routing: Logfare proxies to third-party LLM providers. The
    policy says Logfare does not sell, license, publish, or distribute its
    underlying user-content datasets.
  deletion_controls: Users can object to evaluation use and withdraw future
    training consent; model unlearning is not offered for content already
    trained into a model.
  caveat: “Free” standard access explicitly funds private evaluation data
    collection. Premium routes exchange access for opt-in training use.
privacy:
  logging: Request and response bodies, IP, headers, and metadata are logged.
  standard_tier: May be used for internal evaluation after best-effort PII scrubbing.
  premium_tier: Requires prospective opt-in to model-training use.
agreements:
  terms_of_service: https://logfare.ai/tos
  privacy_policy: https://logfare.ai/privacy
```

## Eligibility

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

## API compatibility and modalities

- **Compatibility:** OpenAI Chat Completions, OpenAI Responses, Anthropic Messages, Embeddings, Images, Audio
- **Modalities:** Text generation, Embeddings, Image / vision, Speech / audio


## Before you build with Logfare

### 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. “Always-free quota” 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

The snapshot records 23 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 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 **Not private** because Every request body is logged and scrubbed content may be used in internal evaluation datasets; premium access can require training opt-in. 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 5 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

- [Logfare](https://logfare.ai/): Official Product
- [API docs](https://logfare.ai/docs): Official Docs
- [Terms](https://logfare.ai/tos): Official Terms
- [Models API](https://logfare.ai/v1/models): Live Catalog
- [Logfare Privacy Policy](https://logfare.ai/privacy): Official Privacy

## Sitemap

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