Hi Bettina Weinmann , I'll try help you as best I can, although I haven't setup this up in Azure, there is a lot of documentation around this from MS to help create minimal walk-through underneath.

Recommended models (balance of quality/speed/cost)

• Default for testing and most production: gpt-4o-mini (OpenAI or Azure OpenAI). Lowest cost, very fast, strong translation quality.
• When quality really matters: gpt-4o. Better handling of nuance/formatting; higher cost and slightly slower.
• Not recommended for MT: o1/o3 (reasoning-focused, slow/expensive) and 3.5 family (older, weaker quality/formatting).

Useful Links

• RWS AppStore (plugin + docs/screenshots): https://appstore.rws.com/ (search “OpenAI Provider”)
• Azure OpenAI access: https://aka.ms/oai/access
• Azure OpenAI model availability by region: https://learn.microsoft.com/azure/ai-services/openai/concepts/models
• Azure OpenAI pricing: https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/
• Data/privacy (Azure OpenAI): https://learn.microsoft.com/azure/ai-services/openai/overview#data-privacy

Quick Azure OpenAI setup (minimal-cost)

1. Access and subscription
   • Ensure your Azure subscription has Azure OpenAI enabled (https://aka.ms/oai/access).
2. Create the resource
   • Azure Portal > Create resource > Azure AI Services > Azure OpenAI.
   • Choose an EU region that has your target model (often West Europe or North Europe; Germany regions may not have all models).
3. Deploy a model
   • Go to Azure AI Foundry (https://ai.azure.com) or the resource in the Portal.
   • Create a Deployment for gpt-4o-mini (or gpt-4o). Give it a short deployment name, e.g., gpt4o-mini.
4. Get connection details
   • From the Azure OpenAI resource: copy Endpoint (looks like https://YOURRESOURCE.openai.azure.com), and one of the Keys.
   • Note the API version your deployment supports (for chat/completions; a recent 2024 date is fine).

Configure the OpenAI Provider in Studio 2024

• Install the OpenAI Provider from the RWS AppStore.
• Studio > Project Settings > Language Pairs > Translation Memory and Automated Translation > Add > OpenAI Provider.
• Choose a backend:
  • OpenAI API: paste your OpenAI API key; Base URL https://api.openai.com/v1; Model gpt-4o-mini or gpt-4o.
  • Azure OpenAI: select Azure; paste Endpoint (root URL only), API key, Deployment name (the one you created), and API version.
• Suggested settings for translation:
  • Temperature: 0.0–0.2 for consistent, non-creative output.
  • Ensure “chat/completions” is used.
• Put the provider near the top of your MT list so it’s queried during interactive translation and pre-translate.

Dear All,

I would appreciate some input from colleagues who have this actually working in Trados Studio 2024 SR1.

I have followed the recommended setup exactly as described:

• Azure OpenAI access enabled

• Azure OpenAI resource created (West Europe)

• Model deployed (gpt-4o-mini)

• Endpoint and API key copied from the Azure OpenAI resource

However, in Trados Studio 2024 SR1 (18.1.3.x), the built-in OpenAI Provider for Trados only exposes a connection form with:

• OpenAI-style model selection (gpt-3.5, gpt-5, etc.)

• Mandatory Reasoning effort

• Model type “Chat Completions (Reasoning)”

• No field for Azure deployment name

As a result, Trados sends OpenAI-native parameters (e.g. reasoning_effort) that are not accepted by Azure OpenAI, leading to 400 errors such as “Unrecognised request: reasoning_effort”.

The documentation suggests that Azure OpenAI can be configured by entering Endpoint, API key and Deployment name, but that Azure-deployment-specific UI does not appear in my Studio 2024 SR1 installation.

My question to the community:
Has anyone successfully connected Azure OpenAI deployments (e.g. gpt-4o-mini) directly to Trados Studio 2024 SR1 using the built-in OpenAI Provider?
If so:

• Which exact Studio build / plugin version are you using?

• Do you see a deployment-based Azure OpenAI configuration screen (without reasoning parameters)?

Any confirmation, workaround, or clarification would be greatly appreciated.

Dear All,

I would appreciate some input from colleagues who have this actually working in Trados Studio 2024 SR1.

I have followed the recommended setup exactly as described:

• Azure OpenAI access enabled

• Azure OpenAI resource created (West Europe)

• Model deployed (gpt-4o-mini)

• Endpoint and API key copied from the Azure OpenAI resource

However, in Trados Studio 2024 SR1 (18.1.3.x), the built-in OpenAI Provider for Trados only exposes a connection form with:

• OpenAI-style model selection (gpt-3.5, gpt-5, etc.)

• Mandatory Reasoning effort

• Model type “Chat Completions (Reasoning)”

• No field for Azure deployment name

As a result, Trados sends OpenAI-native parameters (e.g. reasoning_effort) that are not accepted by Azure OpenAI, leading to 400 errors such as “Unrecognised request: reasoning_effort”.

The documentation suggests that Azure OpenAI can be configured by entering Endpoint, API key and Deployment name, but that Azure-deployment-specific UI does not appear in my Studio 2024 SR1 installation.

My question to the community:
Has anyone successfully connected Azure OpenAI deployments (e.g. gpt-4o-mini) directly to Trados Studio 2024 SR1 using the built-in OpenAI Provider?
If so:

• Which exact Studio build / plugin version are you using?

• Do you see a deployment-based Azure OpenAI configuration screen (without reasoning parameters)?

Any confirmation, workaround, or clarification would be greatly appreciated.