AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed
AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed is a 32 billion parameter chat model from PrunaAI, released January 29, 2025. AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed is an open-weights chat model with roughly 32 billion parameters.
by PrunaAI · 32B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your PrunaAI API key. osFoundry discovers AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed 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
AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed 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 AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed
AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed runs on a 24GB consumer or workstation GPU (~20 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~77 GB).
AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed
Is AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed free to use?
AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed 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 AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed 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 AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed need?
Approximately 20 GB at Q4 quantisation, or 77 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed locally?
Yes. AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed best at?
AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed in osFoundry?
Paste your PrunaAI API key in the key dialog (or deploy the open weights for self-hostable models), assign AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by PrunaAI on January 29, 2025. Source: https://huggingface.co/PrunaAI/AIFunOver-DeepSeek-R1-Distill-Qwen-32B-openvino-8bit-GGUF-smashed