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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.

97,218 次观看 • 1 个月前 •via X (Twitter)

33 条评论

NVIDIA 的头像
NVIDIA1 个月前

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Brent Liang 的头像
Brent Liang1 个月前

@MTSlive so awesome to have kari on the show!

Denys Khomyn 的头像
Denys Khomyn1 个月前

@ChrisJBakke @MTSlive NVIDIA monitoring the situation 🤘

DataVLT 的头像
DataVLT1 个月前

@MTSlive The smarter the routing, the more important the data behind each decision becomes. Model choice is only one part of the stack.

PixelSilicon 的头像
PixelSilicon1 个月前

@MTSlive Model routing by task is becoming essential once agent workflows get multi step. One model for everything is rarely optimal on cost or latency.

KVCacheStore LLC 的头像
KVCacheStore LLC1 个月前

@MTSlive I'm a contributor to Switchyard. If anyone wants help setting it up let me know.

Joel Ramirez 的头像
Joel Ramirez1 个月前

@MTSlive ⚓️✅❌🚀🎇

Glitch Truth 的头像
Glitch Truth1 个月前

@MTSlive Doesn't matter which model wins the routing fight, every single path still ends at an Nvidia GPU.

OGNVDASOL 的头像
OGNVDASOL1 个月前

@MTSlive @elonmusk

Zee B-side 的头像
Zee B-side1 个月前

@MTSlive oxi, now proibida no mundo todo

Ce Ce | AI & Systems Infra 的头像
Ce Ce | AI & Systems Infra1 个月前

@MTSlive model routing based on latency + cost is the part most teams still underestimate

cameron_h23 的头像
cameron_h231 个月前

@MTSlive Model routing is becoming core infrastructure for agent systems—use the expensive reasoning model where it matters, optimize everything else around it.

AI Mastery Guide 的头像
AI Mastery Guide1 个月前

@MTSlive Smart routing saves real money

Robert Hero 的头像
Robert Hero25 天前

@MTSlive The right model depends on the task.

Marissa 的头像
Marissa1 个月前

@MTSlive 👍

J. LEE 的头像
J. LEE1 个月前

@MTSlive Love how NeMo Switchyard lets us pick the perfect model for each step—smart, flexible, and cost‑savvy!

MoM 的头像
MoM1 个月前

@MTSlive

Abhi 的头像
Abhi1 个月前

@MTSlive Routing only works after teams save representative workflows and set a quality floor.

Christopher Dean 的头像
Christopher Dean1 个月前

@MTSlive Per-step routing is right, and it only works if you have per-step evals: without them you're routing on vibes and the cheap model quietly tanks one node of the workflow.

nock 的头像
nock1 个月前

@MTSlive rubin vs tpu pileup this month is the whole story. everyone shipping silicon at once.

Mitchell𖤐⚔️🔺 的头像
Mitchell𖤐⚔️🔺1 个月前

@MTSlive ♻️🔰♻️🔰♻️🔰♻️🔰♻️🔰♻️

Cody Gore 的头像
Cody Gore1 个月前

@MTSlive

Zentiva AI 的头像
Zentiva AI1 个月前

@MTSlive This is a key piece of the agentic AI puzzle. Model routing makes sense when different workflow steps have different requirements. The real challenge is deciding dynamically when quality matters more than latency or cost. That’s where intelligent orchestration becomes critical.

Raul Verdusco 的头像
Raul Verdusco1 个月前

@MTSlive Smart model routing can make agent workflows far more efficient. Matching each task to the right model helps balance quality, latency, and cost without relying on one model for everything.

seastart 的头像
seastart1 个月前

@MTSlive Model routing gets really interesting once you optimize for the whole workflow, not each model in isolation. The best model for one step can be the wrong one for the next.

Greg B 的头像
Greg B1 个月前

@MTSlive Not one person buying this stock. Absolutely makes zero sense why this company is not doubling its stock buyback. Executive leadership screwed investors. This company has an image problem. @JensenHuang

A P E | T H E | N E W S 的头像
A P E | T H E | N E W S1 个月前

@MTSlive Routing is becoming part of model performance, not just infra plumbing. A cheaper model on the right step beats pushing a frontier model through every step blindly.

why 的头像
why1 个月前

@MTSlive Switchyard tackles model routing. Good for balancing quality, latency, cost.

海 的头像
海1 个月前

@MTSlive “NVIDIA is amazing. I just hope it keeps pushing a little harder.”

Raghavan 的头像
Raghavan1 个月前

@MTSlive Yes sir nvidia has great architecture

Вестник 的头像
Вестник1 个月前

@MTSlive Hello @nvidia - why are you helping Russia kill Ukrainians? Do you support mass killing of civilians? In Russian attack drones, Nvidia chips for fully autonomous targeting were found. It was precisely such a drone that killed three civilians in Zaporizhzhia on July 6.

RH Fardin 的头像
RH Fardin1 个月前

@MTSlive Quality, latency, and cost routing per workflow step is the right architecture. GPT should get the hard turns.

mia ♡ 的头像
mia ♡1 个月前

@MTSlive does routing happen per step after failure, or only from the initial plan?

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