Mistral-Large-3-675B-Instruct-2512
Mistral-Large-3-675B-Instruct-2512 (mistralai, 2025) is a 675 billion parameter chat model. Mistral-Large-3-675B-Instruct-2512 is an open-weights chat model with roughly 675 billion parameters.
by mistralai · 675B parameters
Best for
- complex multi-step reasoning
- agent orchestration with tool use
- long-document analysis and summarisation
Ways to use Mistral-Large-3-675B-Instruct-2512 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your mistralai API key. osFoundry discovers Mistral-Large-3-675B-Instruct-2512 automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
Mistral-Large-3-675B-Instruct-2512 is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run Mistral-Large-3-675B-Instruct-2512
Mistral-Large-3-675B-Instruct-2512 runs on a multi-GPU setup or H200 141GB at Q4 (~405 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~1620 GB).
Mistral-Large-3-675B-Instruct-2512 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Mistral-Large-3-675B-Instruct-2512
Is Mistral-Large-3-675B-Instruct-2512 free to use?
Mistral-Large-3-675B-Instruct-2512 is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use Mistral-Large-3-675B-Instruct-2512 commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Mistral-Large-3-675B-Instruct-2512 need?
Approximately 405 GB at Q4 quantisation, or 1620 GB at full FP16 precision. Requires multi-GPU at higher quantisation.
Can I run Mistral-Large-3-675B-Instruct-2512 locally?
Yes. Mistral-Large-3-675B-Instruct-2512 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Mistral-Large-3-675B-Instruct-2512 best at?
Mistral-Large-3-675B-Instruct-2512 is well-suited to complex multi-step reasoning, agent orchestration with tool use, long-document analysis and summarisation.
How do I use Mistral-Large-3-675B-Instruct-2512 in osFoundry?
Paste your mistralai API key in the key dialog (or deploy the open weights for self-hostable models), assign Mistral-Large-3-675B-Instruct-2512 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by mistralai on November 28, 2025. Source: https://huggingface.co/mistralai/Mistral-Large-3-675B-Instruct-2512