Language models

Choose your models, stay in control

OpenAI, Mistral, Anthropic, Gemini or a model you host yourself: a choice per assistant, encrypted keys and a benchmark to decide based on facts.

Supported providers

OpenAI Mistral Anthropic Gemini Ollama vLLM OpenAI-compatible

Same questions, multiple models

For each answer: text, tokens used and latency; Excel export.

Interface diagram: available providers and model comparison (illustrative bars, no actual measurements).

The problem

Why it matters

The model landscape changes every month. Tying your assistants to a single provider exposes you to cost increases, behavior changes or confidentiality constraints.

You need to be able to switch models per assistant, compare them objectively and protect access keys.

In practice

  1. Register credentialsA provider key, or the address of a self-hosted model server, is stored encrypted.
  2. Choose per assistantProvider, model, temperature, response length, reasoning, JSON output.
  3. CompareThe benchmark runs the same questions on several models or versions and measures tokens and latency.

Capabilities

What you can do

Each capability is shown with its actual availability.

  • OpenAI, Mistral, Anthropic, Google GeminiAvailable
  • Ollama, vLLM and OpenAI-compatible servicesSo answers can be generated by a model you host yourself.Available
  • Live model list and connection testAvailable
  • Extended reasoningThinking budget (Anthropic), reasoning effort (OpenAI).Available
  • Structured JSON outputWith an optional JSON schema.Available
  • Encrypted credential vault (AES-256-GCM)Sharing with named users, or availability with a daily cap.Available
  • Multi-model and multi-version benchmarkTokens and latency per question, Excel export.Available
  • Fully offline operationEmbedding, transcription and OCR currently go through OpenAI or Mistral.Experimental

Benefits

What you gain

No vendor lock-in

Switch models without rebuilding your assistants or your knowledge bases.

Evidence-based choices

Compare quality, latency and usage on your own questions.

Protected keys

Encrypted at rest, never exposed to end users.

Requirements and limitations

Next step

Cloud, in-house model servers: what each option means in practice.