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2 changes: 2 additions & 0 deletions ar/guides/features/reasoning-models.mdx
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</CodeGroup>

<Info>
يعيد بعض المزودين (Anthropic، Google، OpenAI، Qwen) tokens تفكير مشفرة أو ملخصة. عندما يحدث هذا، يحتوي `reasoning_content` على عنصر نائب `"[Some reasoning content is encrypted]"`.

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</Info>

### البث
Expand Down Expand Up @@ -124,6 +124,8 @@

### دعم النموذج

تسرد الجداول أدناه النماذج التي يُعرف دعمها لـ `reasoning_effort`. قد تظل نماذج أخرى تولّد توكنات استدلال (تظهر في `usage.completion_tokens_details.reasoning_tokens`) دون أن توفر تحكمًا في مستوى الجهد. للتحقق مما إذا كان نموذج معيّن يدعم الاستدلال أو معلمة `reasoning_effort`، اقرأ حقلَي `supportsReasoning` و`supportsReasoningEffort` في نقطة النهاية [`/v1/models`](/api-reference/endpoint/models/list).

#### OpenAI

| النموذج | القيم المدعومة |
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| النموذج | القيم المدعومة |
|-------|-----------------|
| Qwen 3 235B A22B Thinking, Qwen 3.5 35B A3B | `low`, `medium`, `high` |

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| Kimi K2.5 | `low`, `medium`, `high` |

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| MiniMax M2.5, M2.1 | `low`, `medium`, `high` |
| GLM 5.1 series | تفكير منطقي مدمج فقط، غير قابل للتكوين |
| DeepSeek R1 | تفكير منطقي مدمج فقط، غير قابل للتكوين |
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|-------|-------------|
| GPT-5.2 | نعم |
| GPT-5.2 Codex, GPT-5.3 Codex | نعم (لكن جهد `none` غير مدعوم) |
| Qwen 3 235B A22B Thinking, Qwen 3.5 35B A3B | نعم |

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| GLM 5.1 series | نعم |
| Claude Opus 4.5/4.6/4.6 Fast, Sonnet 4.5/4.6 | لا (يفكر دائمًا) |
| Gemini 3 Pro, 3.1 Pro, 3 Flash | لا (يفكر دائمًا) |
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2 changes: 2 additions & 0 deletions de/guides/features/reasoning-models.mdx
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---
title: "Reasoning-Modelle"
description: "Rufen Sie Venice-Reasoning-Modelle auf, die Chain-of-Thought-Tokens offenlegen, den Denkaufwand steuern und Schritt-für-Schritt-Antworten liefern."

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'og:title': "Reasoning Models | Venice API Docs"
'og:description': "Reasoning-Modelle mit sichtbarem Thinking in der Venice API verwenden"

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---

Einige Modelle "denken laut", bevor sie antworten. Sie arbeiten Probleme Schritt für Schritt durch und geben dann eine finale Antwort. Das macht sie stärker bei Mathematik-, Code- und logiklastigen Aufgaben.

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<div id="reasoning-models-placeholder"></div>

Die vollständige Liste der Modelle, Preise und Kontextlimits finden Sie auf der [Models-Seite](/overview/models). Nicht alle Reasoning-Modelle unterstützen den Parameter [`reasoning_effort`](#reasoning-effort). Siehe [Modellunterstützung](#model-support) für Details.

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## Die Ausgabe lesen

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Reasoning-Modelle geben ihr Thinking in einem separaten Feld `reasoning_content` zurück und halten `content` sauber:

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<CodeGroup>
```python Python
Expand Down Expand Up @@ -48,12 +48,12 @@
</CodeGroup>

<Info>
Einige Anbieter (Anthropic, Google, OpenAI, Qwen) geben verschlüsselte oder zusammengefasste Reasoning-Tokens zurück. In diesem Fall enthält `reasoning_content` einen Platzhalter `"[Some reasoning content is encrypted]"`.

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</Info>

### Streaming

Beim Streaming kommt `reasoning_content` im Delta vor der finalen Antwort an:

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<CodeGroup>
```python Python
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## Reasoning effort

Der Parameter `reasoning_effort` steuert, wie viel ein Modell vor der Antwort denkt. Höherer Effort bedeutet tieferes Reasoning, aber mehr Tokens und Latenz.

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### Akzeptierte Werte

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| Wert | Beschreibung |

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|-------|-------------|
| `none` | Deaktiviert Reasoning vollständig |

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| `minimal` | Grundlegendes Reasoning mit minimalem Aufwand |

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| `low` | Leichtes Reasoning für einfache Probleme |

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| `medium` | Ausgewogenes Reasoning für mittlere Komplexität |

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| `high` | Tiefes Reasoning für komplexe Probleme |

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| `xhigh` | Besonders hohe Reasoning-Tiefe |

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| `max` | Maximale Reasoning-Fähigkeit |

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<Warning>
Nicht alle Modelle unterstützen alle Werte. Venice mappt **nicht** automatisch auf die nächstgelegene unterstützte Stufe. Nicht unterstützte Werte geben einen 400-Fehler vom Upstream-Anbieter zurück. Beispielsweise schlägt das Senden von `xhigh` an Claude oder `max` an GPT-5.2 fehl.

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Verwenden Sie im Zweifel `low`, `medium` oder `high`. Dies sind die am breitesten unterstützten Werte.

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</Warning>

### Modellunterstützung

Die folgenden Tabellen listen Modelle mit bekannter Unterstützung für `reasoning_effort` auf. Andere Modelle können weiterhin Reasoning-Tokens erzeugen (sichtbar in `usage.completion_tokens_details.reasoning_tokens`), ohne eine Effort-Steuerung anzubieten. Um zu prüfen, ob ein bestimmtes Modell Reasoning oder den Parameter `reasoning_effort` unterstützt, lesen Sie die Felder `supportsReasoning` und `supportsReasoningEffort` am Endpoint [`/v1/models`](/api-reference/endpoint/models/list).

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#### OpenAI

| Modell | Unterstützte Werte |

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|-------|-----------------|
| GPT-5.2 | `none`, `low`, `medium`, `high`, `xhigh` |
| GPT-5.2 Codex, GPT-5.3 Codex | `low`, `medium`, `high`, `xhigh` |

#### Anthropic

| Modell | Unterstützte Werte |

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|-------|-----------------|
| Claude Opus 4.6, Opus 4.6 Fast | `low`, `medium`, `high`, `max` |
| Claude Opus 4.5, Sonnet 4.5, Sonnet 4.6 | `low`, `medium`, `high` |

#### Google

| Modell | Unterstützte Werte |

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|-------|-----------------|
| Gemini 3 Pro Preview | `low`, `high` |
| Gemini 3.1 Pro Preview | `low`, `medium`, `high` |
Expand All @@ -148,21 +150,21 @@

#### xAI

Grok-Modelle (Grok 4.1 Fast, Grok Code Fast) unterstützen `reasoning_effort` **nicht**. Die Angabe führt zu einem Fehler.

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#### Weitere Modelle

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| Modell | Unterstützte Werte |

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|-------|-----------------|
| Qwen 3 235B A22B Thinking, Qwen 3.5 35B A3B | `low`, `medium`, `high` |

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| Kimi K2.5 | `low`, `medium`, `high` |

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| MiniMax M2.5, M2.1 | `low`, `medium`, `high` |
| GLM 5.1-Serie | Nur eingebautes Reasoning, nicht konfigurierbar |

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| DeepSeek R1 | Nur eingebautes Reasoning, nicht konfigurierbar |

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### Verwendung

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Übergeben Sie `reasoning_effort` als Top-Level-Parameter oder verwenden Sie das verschachtelte Format `reasoning.effort`:

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<CodeGroup>
```python Python
Expand Down Expand Up @@ -193,28 +195,28 @@
```
</CodeGroup>

Das flache Format `"reasoning_effort": "high"` wird ebenfalls akzeptiert.

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## Reasoning deaktivieren

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Es gibt zwei Möglichkeiten, Reasoning zu deaktivieren:

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| Methode | Syntax | Funktionsweise |

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|--------|--------|-------------|
| `reasoning.enabled: false` | `"reasoning": {"enabled": false}` | Venice-Toggle, der verhindert, dass Reasoning-Parameter an den Anbieter gesendet werden. **Empfohlen.** |

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| `reasoning.effort: "none"` | `"reasoning": {"effort": "none"}` | Wird an den Anbieter weitergegeben, der entscheidet, wie damit umgegangen wird. Nur von einigen Modellen unterstützt (z. B. GPT-5.x). |

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Für Modelle, die es unterstützen, ist `reasoning.enabled: false` die zuverlässigere Option:

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| Modell | Kann deaktiviert werden? |

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|-------|-------------|
| GPT-5.2 | Ja |
| GPT-5.2 Codex, GPT-5.3 Codex | Ja (aber `none`-Effort nicht unterstützt) |

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| Qwen 3 235B A22B Thinking, Qwen 3.5 35B A3B | Ja |

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| GLM 5.1-Serie | Ja |
| Claude Opus 4.5/4.6/4.6 Fast, Sonnet 4.5/4.6 | Nein (immer reasoning) |

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| Gemini 3 Pro, 3.1 Pro, 3 Flash | Nein (immer reasoning) |

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| DeepSeek R1 | Nein (immer reasoning) |

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<CodeGroup>
```python Python
Expand Down Expand Up @@ -247,11 +249,11 @@

## Token-Limits

Reasoning-Modelle generieren sichtbare Antwort-Tokens (in `content`) und Reasoning-Tokens (in `reasoning_content`). Beide zählen zu Ihrem Token-Budget.

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### Eine Token-Obergrenze setzen

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Verwenden Sie `max_completion_tokens`, um die Gesamtzahl der vom Modell generierten Tokens einschließlich Reasoning zu begrenzen:

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```json
{
Expand Down
2 changes: 2 additions & 0 deletions es/guides/features/reasoning-models.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -124,6 +124,8 @@ En caso de duda, usa `low`, `medium` o `high`. Son los valores más ampliamente

### Soporte por modelo

Las tablas siguientes enumeran los modelos con soporte conocido para `reasoning_effort`. Otros modelos pueden seguir generando tokens de razonamiento (visibles en `usage.completion_tokens_details.reasoning_tokens`) sin exponer un control de esfuerzo. Para comprobar si un modelo concreto admite razonamiento o el parámetro `reasoning_effort`, lee los campos `supportsReasoning` y `supportsReasoningEffort` en el endpoint [`/v1/models`](/api-reference/endpoint/models/list).

#### OpenAI

| Modelo | Valores admitidos |
Expand Down
2 changes: 2 additions & 0 deletions fr/guides/features/reasoning-models.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -124,6 +124,8 @@ En cas de doute, utilisez `low`, `medium` ou `high`. Ce sont les valeurs les plu

### Prise en charge des modèles

Les tableaux ci-dessous répertorient les modèles dont la prise en charge de `reasoning_effort` est connue. D'autres modèles peuvent tout de même générer des tokens de raisonnement (visibles dans `usage.completion_tokens_details.reasoning_tokens`) sans exposer de contrôle d'effort. Pour vérifier si un modèle donné prend en charge le raisonnement ou le paramètre `reasoning_effort`, lisez les champs `supportsReasoning` et `supportsReasoningEffort` sur l'endpoint [`/v1/models`](/api-reference/endpoint/models/list).

#### OpenAI

| Modèle | Valeurs prises en charge |
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2 changes: 2 additions & 0 deletions guides/features/reasoning-models.mdx
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Expand Up @@ -124,6 +124,8 @@ When in doubt, use `low`, `medium`, or `high`. These are the most widely support

### Model support

The tables below list models with known `reasoning_effort` support. Other models may still generate reasoning tokens (visible in `usage.completion_tokens_details.reasoning_tokens`) without exposing an effort control. To check whether a specific model supports reasoning or the `reasoning_effort` parameter, read the `supportsReasoning` and `supportsReasoningEffort` fields on the [`/v1/models`](/api-reference/endpoint/models/list) endpoint.

#### OpenAI

| Model | Supported values |
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Expand Up @@ -124,6 +124,8 @@ In caso di dubbi, usa `low`, `medium` o `high`. Sono i valori più ampiamente su

### Supporto dei modelli

Le tabelle seguenti elencano i modelli con supporto noto a `reasoning_effort`. Altri modelli possono comunque generare token di ragionamento (visibili in `usage.completion_tokens_details.reasoning_tokens`) senza esporre un controllo dell'effort. Per verificare se un modello specifico supporta il ragionamento o il parametro `reasoning_effort`, leggi i campi `supportsReasoning` e `supportsReasoningEffort` sull'endpoint [`/v1/models`](/api-reference/endpoint/models/list).

#### OpenAI

| Modello | Valori supportati |
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Expand Up @@ -124,6 +124,8 @@ curl https://api.venice.ai/api/v1/chat/completions \

### 모델 지원

아래 표는 `reasoning_effort`를 지원하는 것으로 알려진 모델을 나열합니다. 다른 모델도 effort 제어를 노출하지 않은 채로 여전히 추론 토큰을 생성할 수 있으며(`usage.completion_tokens_details.reasoning_tokens`에서 확인 가능), 특정 모델이 추론이나 `reasoning_effort` 파라미터를 지원하는지 확인하려면 [`/v1/models`](/api-reference/endpoint/models/list) 엔드포인트의 `supportsReasoning` 및 `supportsReasoningEffort` 필드를 읽으세요.

#### OpenAI

| Model | Supported values |
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17 changes: 15 additions & 2 deletions overview/pricing.mdx
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@@ -1,11 +1,22 @@
---
title: API Pricing
title: Venice API Pricing
description: "Venice API pricing per 1M tokens for text, image, video, audio, and embedding models, plus credit costs for web search, RPC calls, and other services."
"og:title": "Pricing | Venice API Docs"
"og:description": "Learn about pricing for Venice's API."
"og:description": "Learn about Venice API pricing per 1M tokens across text, image, video, audio, and embedding models."
---

Prices per 1M tokens unless noted. All prices in USD. 1 Diem = $1/day of compute.

## How the API bills

The Venice API is **pay-as-you-go**: every request is metered and debited from your account's Venice credit balance (funded in USD or via staked DIEM). There is no free tier, no monthly API allowance, and no login-based subscription plan for the API. Access is authenticated by API key and billed per request.

<Note>
The Free, Pro, and Max plans on the [venice.ai](https://venice.ai) consumer apps (web, desktop, and mobile chat) are separate from the API. Consumer subscription allowances such as image counts, character quotas, and unlimited chat apply only to those apps and do **not** apply to API usage. API calls are always metered from your Venice credit balance regardless of your consumer plan. See [Pro Users](#pro-users) below for the one-time credit Pro subscribers receive.
</Note>

To use the API, you need an [API key](/guides/getting-started/generating-api-key) and available balance, funded through one of the [Payment Options](#payment-options) below. Every model listed on this page is available to any API key with sufficient balance. There is no separate "base" versus "Pro" model split on the API.

## Text Models

### Chat Completions
Expand Down Expand Up @@ -478,3 +489,5 @@ These charges apply in addition to standard model token pricing.
### Pro Users

Pro subscribers receive a one-time $10 Venice credit when upgrading to Pro. Use it to test and build small apps.

Beyond that credit, API usage continues to be billed at the same pay-as-you-go rates listed above. A Pro subscription does not include additional API allowances such as bundled images, characters, or tokens. Some models are restricted to Pro accounts (`PRO_ONLY_MODEL`); calling them from an account without an active Pro subscription returns `AUTHENTICATION_FAILED_INACTIVE_KEY`. See [Error Codes](/api-reference/error-codes).
2 changes: 2 additions & 0 deletions pt-BR/guides/features/reasoning-models.mdx
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Expand Up @@ -124,6 +124,8 @@ Em caso de dúvida, use `low`, `medium` ou `high`. Esses são os valores mais am

### Suporte por modelo

As tabelas abaixo listam os modelos com suporte conhecido a `reasoning_effort`. Outros modelos ainda podem gerar tokens de raciocínio (visíveis em `usage.completion_tokens_details.reasoning_tokens`) sem expor um controle de esforço. Para verificar se um modelo específico suporta raciocínio ou o parâmetro `reasoning_effort`, leia os campos `supportsReasoning` e `supportsReasoningEffort` no endpoint [`/v1/models`](/api-reference/endpoint/models/list).

#### OpenAI

| Modelo | Valores suportados |
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### 模型支持

下表列出了已知支持 `reasoning_effort` 的模型。其他模型仍可能生成推理 token(可在 `usage.completion_tokens_details.reasoning_tokens` 中查看),但不提供 effort 控制。要查看特定模型是否支持推理或 `reasoning_effort` 参数,请读取 [`/v1/models`](/api-reference/endpoint/models/list) 端点上的 `supportsReasoning` 和 `supportsReasoningEffort` 字段。

#### OpenAI

| 模型 | 支持的值 |
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