---
title: "ch.at free inference"
description: "Community-supplied inference across 1 model; capacity varies and throughput is not guaranteed."
canonical_url: "https://freeinferencing.com/provider/ch_at/"
md_url: "https://freeinferencing.com/provider/ch_at.md"
last_updated: "2026-09-19"
---

# ch.at

> Community-supplied inference across 1 model; capacity varies and throughput is not guaranteed.

## Classification

- **Directory:** Current
- **Free access:** Community capacity
- **Status:** Community service
- **Confidence:** High
- **Payment card:** No
- **Account:** Not required
- **Equivalent paid value:** Not quantifiable
- **API endpoint:** `https://ch.at/v1`

## Models mentioned

- `default`

## Limits and terms

```yaml
requests_per_minute_per_ip: 100
burst: 10
history_cap: 64KB
```

## What happens to your prompts?

**Partially private.** The service claims no logs, but the current upstream model and its data handling are 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: Anonymous ch.at web, curl, DNS, SSH, and API access.
  prompt_retention: The service states “No logs”; no prompt history or account is provided.
  response_retention: The same no-logs claim applies to responses in ordinary operation.
  ordinary_logging: ch.at explicitly markets no logs and no accounts, though no
    separately negotiated audit or DPA was found.
  model_training: No training use is disclosed; the no-logs architecture would
    preclude retained-content training by ch.at in ordinary operation.
  product_improvement: No content-based improvement use is disclosed.
  human_or_operator_access: Requests are necessarily processed in plaintext by the
    service during inference; no zero-operator-access claim is made.
  subprocessors_and_routing: The public repository and deployed service should be
    checked for current model/upstream configuration; upstream handling is not
    fully documented in the privacy page.
  deletion_controls: No stored content is claimed, so no content-deletion control
    is offered; there is no user account.
  caveat: “No logs” is a first-party operational claim, not an independently
    audited contractual SLA, and upstream model handling remains unclear.
agreements:
  privacy_policy: https://ch.at/privacy
```

## Eligibility

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

## API compatibility and modalities

- **Compatibility:** OpenAI Chat Completions
- **Modalities:** Text generation


## Before you build with ch.at

### 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. “Community capacity” 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 1 model ID. 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 not 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 The service claims no logs, but the current upstream model and its data handling are 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 3 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

- [ch.at repository](https://github.com/Deep-ai-inc/ch.at): Official Repository
- [Chat completions endpoint](https://ch.at/v1/chat/completions): Live Endpoint
- [ch.at privacy response](https://ch.at/privacy): Official Privacy

## Sitemap

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