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EN update virtual model doc to highlight its dynamicity #8483

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EN update virtual model doc to highlight its dynamicity
Oct 6, 2025
5707eb5
FR update virtual model doc to highlight its dynamicity
Oct 6, 2025
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Y0Coss Oct 6, 2025
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Y0Coss Oct 6, 2025
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15 changes: 10 additions & 5 deletions ...blic_cloud/ai_machine_learning/endpoints_guide_07_virtual_models/guide.en-gb.md
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@@ -1,7 +1,7 @@
---
title: AI Endpoints - Using Virtual Models
excerpt: Learn how to use OVHcloud AI Endpoints Virtual Models
updated: 2025-08-18
updated: 2025-10-12
---

> [!primary]
Expand Down Expand Up @@ -42,6 +42,11 @@ Follow the instructions in the [AI Endpoints - Getting Started](/pages/public_cl

## Model DSL

> [!warning]
>
> As our virtual model feature allows dynamic model switching, the model’s characteristics (including pricing or context size) may change when a newer model is selected to handle your query. If you prefer certain features to remain fixed, you can lock them using the query conditions listed below.
>

When you request an LLM generation through our unified endpoint, you can provide in the OpenAI-compliant `model` field a model DSL query instead of a hardcoded model name.

These queries are divided into three parts: tag, ranker, and condition:
Expand All @@ -54,10 +59,10 @@ Below are some example queries and the models they currently resolve to. Please

| Model Query | Current Target Model | Usage |
|-----------|-----------|-----------|
| code_chat@latest | Qwen3-32B | The most recently released model optimized for code chat tasks |
| meta-llama@latest | Llama-3.1-8B-Instruct | The latest Meta-released LLaMA model |
| mistral@latest?context_size > 100000 | Mistral-Small-3.2-24B-Instruct-2506 | The latest Mistral model with a context window greater than 100k tokens |
| llama@biggest?input_cost<0.5 | Llama-3.1-8B-Instruct | The largest LLaMA model whose input token cost is under €0.50 per 1M tokens |
| code_chat@latest | **Example:** Qwen3-32B | The most recently released model optimized for code chat tasks |
| meta-llama@latest | **Example:** Llama-3.1-8B-Instruct | The latest Meta-released LLaMA model |
| mistral@latest?context_size > 100000 | **Example:** Mistral-Small-3.2-24B-Instruct-2506 | The latest Mistral model with a context window greater than 100k tokens |
| llama@biggest?input_cost<0.5 | **Example:** Llama-3.1-8B-Instruct | The largest LLaMA model whose input token cost is under €0.50 per 1M tokens |

You can visit our [catalog](https://endpoints.ai.cloud.ovh.net/catalog) to learn more about the different model specifications.

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18 changes: 11 additions & 7 deletions ...blic_cloud/ai_machine_learning/endpoints_guide_07_virtual_models/guide.fr-fr.md
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
---
title: AI Endpoints - Modèles virtuels
excerpt: "Découvrez comment utiliser les modèles virtuels d'AI Endpoints"
updated: 2025-08-18
updated: 2025-10-12
---

> [!primary]
Expand Down Expand Up @@ -42,6 +42,11 @@ Follow the instructions in the [AI Endpoints - Getting Started](/pages/public_cl

## Model DSL

> [!warning]
>
> As our virtual model feature allows dynamic model switching, the model’s characteristics (including pricing or context size) may change when a newer model is selected to handle your query. If you prefer certain features to remain fixed, you can lock them using the query conditions listed below.
>

When you request an LLM generation through our unified endpoint, you can provide in the OpenAI-compliant `model` field a model DSL query instead of a hardcoded model name.

These queries are divided into three parts: tag, ranker, and condition:
Expand All @@ -54,10 +59,10 @@ Below are some example queries and the models they currently resolve to. Please

| Model Query | Current Target Model | Usage |
|-----------|-----------|-----------|
| code_chat@latest | Qwen3-32B | The most recently released model optimized for code chat tasks |
| meta-llama@latest | Llama-3.1-8B-Instruct | The latest Meta-released LLaMA model |
| mistral@latest?context_size > 100000 | Mistral-Small-3.2-24B-Instruct-2506 | The latest Mistral model with a context window greater than 100k tokens |
| llama@biggest?input_cost<0.5 | Llama-3.1-8B-Instruct | The largest LLaMA model whose input token cost is under €0.50 per 1M tokens |
| code_chat@latest | **Example:** Qwen3-32B | The most recently released model optimized for code chat tasks |
| meta-llama@latest | **Example:** Llama-3.1-8B-Instruct | The latest Meta-released LLaMA model |
| mistral@latest?context_size > 100000 | **Example:** Mistral-Small-3.2-24B-Instruct-2506 | The latest Mistral model with a context window greater than 100k tokens |
| llama@biggest?input_cost<0.5 | **Example:** Llama-3.1-8B-Instruct | The largest LLaMA model whose input token cost is under €0.50 per 1M tokens |

You can visit our [catalog](https://endpoints.ai.cloud.ovh.net/catalog) to learn more about the different model specifications.

Expand Down Expand Up @@ -141,5 +146,4 @@ If you need training or technical assistance to implement our solutions, contact

Please send us your questions, feedback and suggestions to improve the service:

- On the OVHcloud [Discord server](https://discord.gg/ovhcloud).

- On the OVHcloud [Discord server](https://discord.gg/ovhcloud).