m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10
Released by dervig in 2026, m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 is a 139 billion parameter chat model. m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 is an open-weights chat model with roughly 139 billion parameters.
by dervig · 139B parameters
Best for
Ways to use m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your dervig API key. osFoundry discovers m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 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
m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 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 m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10
m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 runs on a multi-GPU setup or H200 141GB at Q4 (~84 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~334 GB).
m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10
Is m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 free to use?
m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 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 m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 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 m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 need?
Approximately 84 GB at Q4 quantisation, or 334 GB at full FP16 precision. Requires multi-GPU at higher quantisation.
Can I run m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 locally?
Yes. m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 best at?
m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 is well-suited to text generation.
How do I use m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 in osFoundry?
Paste your dervig API key in the key dialog (or deploy the open weights for self-hostable models), assign m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by dervig on April 16, 2026. Source: https://huggingface.co/dervig/m51Lab-MiniMax-M2.7-REAP-139B-A10B-NVFP4-GB10