DeepSeek-V3.2-REAP-345B-W3A16
DeepSeek-V3.2-REAP-345B-W3A16 (0xSero, 2026) is a 345 billion parameter chat model. DeepSeek-V3.2-REAP-345B-W3A16 is an open-weights chat model with roughly 345 billion parameters.
by 0xSero · 345B parameters
Best for
Ways to use DeepSeek-V3.2-REAP-345B-W3A16 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your 0xSero API key. osFoundry discovers DeepSeek-V3.2-REAP-345B-W3A16 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
DeepSeek-V3.2-REAP-345B-W3A16 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 DeepSeek-V3.2-REAP-345B-W3A16
DeepSeek-V3.2-REAP-345B-W3A16 runs on a multi-GPU setup or H200 141GB at Q4 (~207 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~828 GB).
DeepSeek-V3.2-REAP-345B-W3A16 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about DeepSeek-V3.2-REAP-345B-W3A16
Is DeepSeek-V3.2-REAP-345B-W3A16 free to use?
DeepSeek-V3.2-REAP-345B-W3A16 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 DeepSeek-V3.2-REAP-345B-W3A16 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 DeepSeek-V3.2-REAP-345B-W3A16 need?
Approximately 207 GB at Q4 quantisation, or 828 GB at full FP16 precision. Requires multi-GPU at higher quantisation.
Can I run DeepSeek-V3.2-REAP-345B-W3A16 locally?
Yes. DeepSeek-V3.2-REAP-345B-W3A16 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is DeepSeek-V3.2-REAP-345B-W3A16 best at?
DeepSeek-V3.2-REAP-345B-W3A16 is well-suited to text generation.
How do I use DeepSeek-V3.2-REAP-345B-W3A16 in osFoundry?
Paste your 0xSero API key in the key dialog (or deploy the open weights for self-hostable models), assign DeepSeek-V3.2-REAP-345B-W3A16 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by 0xSero on January 3, 2026. Source: https://huggingface.co/0xSero/DeepSeek-V3.2-REAP-345B-W3A16