Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Sub-agent Model Selection — Different Tasks, Different Models Your main agent runs Qwen3.6-Plus for quality. But not every subtask needs a flagship model. Now sub-agents can use a different model. Create a skill file with model: openai:qwen3.5-plus and the sub-agent runs on that model. Powerful model for the hard...

Alibaba_Qwen's profile picture

Qwen

210,371 subscribers

21,333 Aufrufe • vor 5 Monaten •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.
1:53

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

QVAC

11,382,936 Aufrufe • vor 2 Monaten

...Am I the only one hand-rolling my PR review agent? It's so easy to do: - Write a /pr-review skill with the formatting you want - Add a GitHub workflow that runs your agent of choice, ideally a different model from your primary agent to find gaps in thinking Done!
0:23

...Am I the only one hand-rolling my PR review agent? It's so easy to do: - Write a /pr-review skill with the formatting you want - Add a GitHub workflow that runs your agent of choice, ideally a different model from your primary agent to find gaps in thinking Done!

Ben Holmes

14,322 Aufrufe • vor 1 Monat

A lot of people are calling Hermes Agent the end of OpenClaw. BRUH! It's not... Nous Research trains actual models and they built an agent around that expertise. The local model routing is solid, but the part that matters for your business is that your conversations become fine-tuning data. You can train a model on how you actually work. 00:00 The Problem with Local AI Models 00:25 Introduction to Nous Research 01:04 Cross-Platform Agent Capabilities 01:44 Deep Local Model Integration 02:30 Routing Tasks to Different Models 03:06 Conversations as Training Data 03:50 Hermes Agent vs. OpenClaw 04:15 Future Plans and Series Overview
4:45

A lot of people are calling Hermes Agent the end of OpenClaw. BRUH! It's not... Nous Research trains actual models and they built an agent around that expertise. The local model routing is solid, but the part that matters for your business is that your conversations become fine-tuning data. You can train a model on how you actually work. 00:00 The Problem with Local AI Models 00:25 Introduction to Nous Research 01:04 Cross-Platform Agent Capabilities 01:44 Deep Local Model Integration 02:30 Routing Tasks to Different Models 03:06 Conversations as Training Data 03:50 Hermes Agent vs. OpenClaw 04:15 Future Plans and Series Overview

Ray Fernando

42,398 Aufrufe • vor 5 Monaten

The right model depends on the task. NVIDIA NeMo Switchyard helps developers route each agent workflow step across a chosen model pool based on their own quality, latency and cost criteria. Kari Briski joins MTS to explain why agent workflows need model routing.
0:23

The right model depends on the task. NVIDIA NeMo Switchyard helps developers route each agent workflow step across a chosen model pool based on their own quality, latency and cost criteria. Kari Briski joins MTS to explain why agent workflows need model routing.

NVIDIA

94,363 Aufrufe • vor 18 Tagen

ICYMI: Not every step in an agent workflow needs the same model. Meet NVIDIA NeMo Switchyard, a new open-source library for model routing. Use frontier models for complex reasoning and planning, and NVIDIA Nemotron Lightning for high-volume, specialized execution.
6:06

ICYMI: Not every step in an agent workflow needs the same model. Meet NVIDIA NeMo Switchyard, a new open-source library for model routing. Use frontier models for complex reasoning and planning, and NVIDIA Nemotron Lightning for high-volume, specialized execution.

NVIDIA AI

14,777 Aufrufe • vor 24 Tagen

Factory benchmarks let you build your own model bench using your past coding agent runs. - Mirrors your environment, secrets, and MCPs for each run - Scores output on judging criteria you define - Generates a report with model recs using cost vs. quality Here's how it works:
6:05

Factory benchmarks let you build your own model bench using your past coding agent runs. - Mirrors your environment, secrets, and MCPs for each run - Scores output on judging criteria you define - Generates a report with model recs using cost vs. quality Here's how it works:

Warp

71,982 Aufrufe • vor 4 Tagen

Introducing UI-TARS-1.5, a vision-language model that beats OpenAI Operator and Claude 3.7 on GUI Agent and Game Agent tasks. We've open-sourced a small-size version model for research purposes, more details can be found in our blog. TARS learns solely from a screen, but generalizes beyond a screen! Blog: Model: App:
1:17

Introducing UI-TARS-1.5, a vision-language model that beats OpenAI Operator and Claude 3.7 on GUI Agent and Game Agent tasks. We've open-sourced a small-size version model for research purposes, more details can be found in our blog. TARS learns solely from a screen, but generalizes beyond a screen! Blog: Model: App:

Yujia Qin

85,212 Aufrufe • vor 1 Jahr

The best open source agent, now better with multi-model Chat. The latest release of II-Agent lets you use any model or subscription to build anything you can imagine. Use multiple models (Gemini 3 etc etc) on chat or build anything you can imagine with the agent.
0:31

The best open source agent, now better with multi-model Chat. The latest release of II-Agent lets you use any model or subscription to build anything you can imagine. Use multiple models (Gemini 3 etc etc) on chat or build anything you can imagine with the agent.

Intelligent Internet

125,774 Aufrufe • vor 9 Monaten

Create your own local and free AI agent using an open source model You can combine: - IBM's Granite 3.3 8B AI model - LM Studio to run it on a laptop - Smolagents to build your agent Small AI models are now powerful enough to run an autonomous agent. Thanks to IBM France for sponsoring this content!
8:44

Create your own local and free AI agent using an open source model You can combine: - IBM's Granite 3.3 8B AI model - LM Studio to run it on a laptop - Smolagents to build your agent Small AI models are now powerful enough to run an autonomous agent. Thanks to IBM France for sponsoring this content!

Paul Couvert

18,890 Aufrufe • vor 1 Jahr

The munchkin model is almost finished! It will be a little while before it's out on gumroad, but I just added the option to randomize the model so you can play around with the different parts! 😻
0:29

The munchkin model is almost finished! It will be a little while before it's out on gumroad, but I just added the option to randomize the model so you can play around with the different parts! 😻

Teevz🌸

10,378 Aufrufe • vor 6 Monaten

Liquid AI's head of post-training explained how they built a small model that runs on-device under 1 GB in 20 minutes - better than $2500 small-model bootcamps. pick LFM2.5 base -> on-policy preference alignment -> agentic reinforcement learning -> curriculum training -> iterative model merging -> ship a 1B model that reliably calls tools on your phone. That loop is why frontier small models now beat 70B models on the tasks that actually matter. LFM2.5 + on-policy DPO + agentic RL + curriculum training + iterative merging - that's the stack. Watch and save it, then run a 1B agent on your phone tonight.
19:11

Liquid AI's head of post-training explained how they built a small model that runs on-device under 1 GB in 20 minutes - better than $2500 small-model bootcamps. pick LFM2.5 base -> on-policy preference alignment -> agentic reinforcement learning -> curriculum training -> iterative model merging -> ship a 1B model that reliably calls tools on your phone. That loop is why frontier small models now beat 70B models on the tasks that actually matter. LFM2.5 + on-policy DPO + agentic RL + curriculum training + iterative merging - that's the stack. Watch and save it, then run a 1B agent on your phone tonight.

h100envy

86,913 Aufrufe • vor 1 Monat

With Intelligent Model Routing, Replit picks the model for every task you send, so you can operate with quality, speed, and efficiency, at no extra cost. Here’s how it works, plus a breakdown on the difference between Free, Power and Max ↓
2:51

With Intelligent Model Routing, Replit picks the model for every task you send, so you can operate with quality, speed, and efficiency, at no extra cost. Here’s how it works, plus a breakdown on the difference between Free, Power and Max ↓

Replit ⠕

11,941 Aufrufe • vor 11 Tagen

Not every AI interaction is best served with a large frontier model. There is a long tail of trillion-token use cases, from tagging to search, best served by a sub-10b-parameter model that runs in milliseconds and costs many orders of magnitude less than the frontier. We built Freesolo Flash to make training loops like SFT and RL easy and end-to-end completable through your coding agent.
2:02

Not every AI interaction is best served with a large frontier model. There is a long tail of trillion-token use cases, from tagging to search, best served by a sub-10b-parameter model that runs in milliseconds and costs many orders of magnitude less than the frontier. We built Freesolo Flash to make training loops like SFT and RL easy and end-to-end completable through your coding agent.

Freesolo

28,663 Aufrufe • vor 1 Monat

OpenAI just killed the idea of one best model. GPT-5.6 is three different jobs: - Sol for hard reasoning and long agent runs - Terra for everyday work - Luna for cheap high-volume tasks Most people will send every prompt to Sol, then complain about the cost. The edge is not having the flagship. It is knowing when you do not need it.
1:24

OpenAI just killed the idea of one best model. GPT-5.6 is three different jobs: - Sol for hard reasoning and long agent runs - Terra for everyday work - Luna for cheap high-volume tasks Most people will send every prompt to Sol, then complain about the cost. The edge is not having the flagship. It is knowing when you do not need it.

Fluixo

12,641 Aufrufe • vor 1 Monat

"The model is no longer the product. Codex, Perplexity Computer, or Claude Code - all are orchestration system. It takes a model and pairs it with an agent harness. What is an agent harness ? The rules for how the agent loops around" - Aravind Srinivas
3:27

"The model is no longer the product. Codex, Perplexity Computer, or Claude Code - all are orchestration system. It takes a model and pairs it with an agent harness. What is an agent harness ? The rules for how the agent loops around" - Aravind Srinivas

Rohan Paul

120,488 Aufrufe • vor 2 Monaten

Hermes Agent is now free to run 24/7. No paid model needed. You can plug in: → Qwen 3.6 Plus → OwlAlpha via OpenRouter Both have 1M token context windows. That means your agent can research, write, find leads, handle tasks, and build workflows without burning through paid API credits. The best part? When one free model hits limits, just switch to the other. Free AI agents are getting scary fast.
8:29

Hermes Agent is now free to run 24/7. No paid model needed. You can plug in: → Qwen 3.6 Plus → OwlAlpha via OpenRouter Both have 1M token context windows. That means your agent can research, write, find leads, handle tasks, and build workflows without burning through paid API credits. The best part? When one free model hits limits, just switch to the other. Free AI agents are getting scary fast.

Julian Goldie SEO

21,609 Aufrufe • vor 3 Monaten

Here is the progress with my munchkin model! It's a modular setup where you can mix and match different parts. Next on the list is to make proper textures (there will be 8 sets on the final model!) :D #vrchat #lowpoly #3d
1:15

Here is the progress with my munchkin model! It's a modular setup where you can mix and match different parts. Next on the list is to make proper textures (there will be 8 sets on the final model!) :D #vrchat #lowpoly #3d

Teevz🌸

101,825 Aufrufe • vor 6 Monaten

Watch Devin Fusion work: The sidekick model handles fetching information and skimming sources. The frontier model makes a plan for implementation, then delegates well-scoped sub-tasks to the sidekick with its own cached context.
0:28

Watch Devin Fusion work: The sidekick model handles fetching information and skimming sources. The frontier model makes a plan for implementation, then delegates well-scoped sub-tasks to the sidekick with its own cached context.

Cognition

25,080 Aufrufe • vor 2 Monaten