StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln
StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln is a chat model from mengwei0427, released July 8, 2025. StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln is an open-weights chat model.
by mengwei0427
Best for
Ways to use StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your mengwei0427 API key. osFoundry discovers StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln 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
StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln 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.
StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln vs similar models
| Model | Org | Params | Context | Input price | Self-host |
|---|
| StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln | mengwei0427 | — | — | Free (local) | Yes |
| gemma-2-2b_math | MergeBench | — | — | Free (local) | Yes |
| granite-4.0-h-small-GGUF | lmstudio-community | — | — | Free (local) | Yes |
| Medra-GGUF | mradermacher | — | — | Free (local) | Yes |
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln
Is StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln free to use?
StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln 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 StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln locally?
Yes. StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln best at?
StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln is well-suited to robotics.
How do I use StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln in osFoundry?
Paste your mengwei0427 API key in the key dialog (or deploy the open weights for self-hostable models), assign StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by mengwei0427 on July 8, 2025. Source: https://huggingface.co/mengwei0427/StreamVLN_Video_qwen_1_5_r2r_rxr_envdrop_scalevln