Models · Mistral AI

Deploy Mistral AI models on dedicated GPUs

12 Mistral AI models ready to deploy on GPU capacity reserved for you, from 4.4B to 125B parameters, covering chat & reasoning, coding, speech recognition and text-to-speech. Private OpenAI-compatible endpoint, European GPUs, billed per GPU-hour.

ModelParams
Mistral AI4.4B
Mistral AI—
Mistral AI4.7B
Mistral AI24B
Mistral AI24B
Mistral AI24B
Mistral AI119B
Mistral AI14B
Mistral AI125B
Mistral AI24B
Mistral AI—
Mistral AI8.9B

Specs from Hugging Face, synced 2026-10-27. Machine-readable version: https://sference.com/models/mistralai.md

FAQ

Which Mistral AI models can I deploy on sference?

12 today, most requested first: Voxtral-Mini-4B-Realtime-2602, Voxtral-4B-TTS-2603, Voxtral-Mini-3B-2507, Devstral-Small-2-24B-Instruct-2512, Voxtral-Small-24B-2507, Mistral-Small-3.2-24B-Instruct-2506, Mistral-Small-4-119B-2603 and Ministral-3-14B-Instruct-2512, and 4 more. Any other Mistral AI checkpoint or a fine-tune of one can be requested with the form on this page.

How many GPUs do Mistral AI models need?

It depends on the model: the lineup runs from 4.4B to 125B parameters. Each model page lists the checkpoint size and the minimum footprint on 80 GB and 141 GB GPUs. You don't pick hardware on sference: you choose a performance tier and we size the deployment.

Can I use Mistral AI models commercially?

10 of the 12 listed models are under licenses that allow commercial use (Apache 2.0, CC BY-NC 4.0 and Custom license across the lineup). Each model page summarizes its license and links the full text.

How is a dedicated deployment priced?

Per GPU-hour on a monthly commitment, sized to your throughput and latency targets.

Request a Mistral AI model

Tell us which Mistral AI model and roughly how much traffic you expect. Fine-tunes of these models work the same way.

  1. 01
    We size it

    A performance tier, the capacity behind it, and a quote for your volume.

  2. 02
    We benchmark it

    Bring one workload with a sample of real traffic; we come back with latency and throughput numbers.

  3. 03
    It goes live

    We provision the deployment. You call it with the same API and model id as before.

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