MOSS-Audio-8B-Thinking
Built by OpenMOSS-Team, MOSS-Audio-8B-Thinking is a 8 billion parameter speech-and-audio model. MOSS-Audio-8B-Thinking is an open-weights audio model with roughly 8 billion parameters.
by OpenMOSS-Team · 8B parameters
Best for
Ways to use MOSS-Audio-8B-Thinking in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your OpenMOSS-Team API key. osFoundry discovers MOSS-Audio-8B-Thinking 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
MOSS-Audio-8B-Thinking 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 MOSS-Audio-8B-Thinking
MOSS-Audio-8B-Thinking runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~20 GB).
MOSS-Audio-8B-Thinking vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about MOSS-Audio-8B-Thinking
Is MOSS-Audio-8B-Thinking free to use?
MOSS-Audio-8B-Thinking 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 MOSS-Audio-8B-Thinking 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 MOSS-Audio-8B-Thinking need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run MOSS-Audio-8B-Thinking locally?
Yes. MOSS-Audio-8B-Thinking is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is MOSS-Audio-8B-Thinking best at?
MOSS-Audio-8B-Thinking is well-suited to audio text to text.
How do I use MOSS-Audio-8B-Thinking in osFoundry?
Paste your OpenMOSS-Team API key in the key dialog (or deploy the open weights for self-hostable models), assign MOSS-Audio-8B-Thinking to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by OpenMOSS-Team on April 13, 2026. Source: https://huggingface.co/OpenMOSS-Team/MOSS-Audio-8B-Thinking