Mixtral_7Bx4_MOE_24B
Mixtral_7Bx4_MOE_24B is a 24 billion parameter chat model from cloudyu, released December 21, 2023. Mixtral_7Bx4_MOE_24B is an open-weights chat model with roughly 24 billion parameters.
by cloudyu · 24B parameters
Best for
Ways to use Mixtral_7Bx4_MOE_24B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your cloudyu API key. osFoundry discovers Mixtral_7Bx4_MOE_24B 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
Mixtral_7Bx4_MOE_24B 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 Mixtral_7Bx4_MOE_24B
Mixtral_7Bx4_MOE_24B runs on a single 16GB consumer GPU (~15 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~58 GB).
Mixtral_7Bx4_MOE_24B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Mixtral_7Bx4_MOE_24B
Is Mixtral_7Bx4_MOE_24B free to use?
Mixtral_7Bx4_MOE_24B 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 Mixtral_7Bx4_MOE_24B 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 Mixtral_7Bx4_MOE_24B need?
Approximately 15 GB at Q4 quantisation, or 58 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Mixtral_7Bx4_MOE_24B locally?
Yes. Mixtral_7Bx4_MOE_24B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Mixtral_7Bx4_MOE_24B best at?
Mixtral_7Bx4_MOE_24B is well-suited to text generation.
How do I use Mixtral_7Bx4_MOE_24B in osFoundry?
Paste your cloudyu API key in the key dialog (or deploy the open weights for self-hostable models), assign Mixtral_7Bx4_MOE_24B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by cloudyu on December 21, 2023. Source: https://huggingface.co/cloudyu/Mixtral_7Bx4_MOE_24B