InternVideo2_5_Chat_8B
Released by OpenGVLab in 2025, InternVideo2_5_Chat_8B is a 8 billion parameter video-generation model. InternVideo2_5_Chat_8B is an open-weights video model with roughly 8 billion parameters.
by OpenGVLab · 8B parameters
Best for
Ways to use InternVideo2_5_Chat_8B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your OpenGVLab API key. osFoundry discovers InternVideo2_5_Chat_8B 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
InternVideo2_5_Chat_8B 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 InternVideo2_5_Chat_8B
InternVideo2_5_Chat_8B 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).
InternVideo2_5_Chat_8B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about InternVideo2_5_Chat_8B
Is InternVideo2_5_Chat_8B free to use?
InternVideo2_5_Chat_8B 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 InternVideo2_5_Chat_8B 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 InternVideo2_5_Chat_8B need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run InternVideo2_5_Chat_8B locally?
Yes. InternVideo2_5_Chat_8B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is InternVideo2_5_Chat_8B best at?
InternVideo2_5_Chat_8B is well-suited to video text to text.
How do I use InternVideo2_5_Chat_8B in osFoundry?
Paste your OpenGVLab API key in the key dialog (or deploy the open weights for self-hostable models), assign InternVideo2_5_Chat_8B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by OpenGVLab on January 22, 2025. Source: https://huggingface.co/OpenGVLab/InternVideo2_5_Chat_8B