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Introducing VisionPsy-Nano: state-of-the-art vision-language models at 460M parameters, small enough to run on the phone in your pocket. VisionPsy-Nano-460M leads every other ~0.5B vision-language model tested & compares favourably on 16 of 17 benchmarks, tops all four capability categories, and outperforms models up to 2.3x larger. Two variants, one... show more

QVAC

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15,329,496 Aufrufe • vor 1 Monat •via X (Twitter)

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29 Kommentare

Profilbild von QVAC

QVACvor 1 Monat

Everything is out today: open weights, the blog, and the full benchmark breakdown. Model weights: Hugging Face Blog :

Profilbild von adidshaft

adidshaftvor 1 Monat

does the 0.3s iPhone TTFT include image decode and resize, or does timing start once the 512x512 tensor is ready?

Profilbild von just soph

just sophvor 1 Monat

wait can i run this on my iphone?

Profilbild von Ryan White

Ryan Whitevor 1 Monat

Open weights, runs on a phone, beats models 2.3x its size. Brussels still drafting rules for models that won't exist by the time they finish.

Profilbild von AI Mastery Guide

AI Mastery Guidevor 1 Monat

460M beating models 2x its size is genuinely impressive

Profilbild von smiks

smiksvor 1 Monat

@woxshter le goat

Profilbild von med halbaj

med halbajvor 1 Monat

Gibraltar est européenne mais Ceuta et Melilla sont africaine

Profilbild von sophs b.

sophs b.vor 1 Monat

how's it compare to the phi-3 vision models at similar size?

Profilbild von DeFiDave

DeFiDavevor 1 Monat

Wow

Profilbild von Rompel

Rompelvor 1 Monat

460M leading its class on-device is real. But "leads every benchmark" self-scored needs a number. The story is decode tok/s + prefill on actual phone silicon—and the SigLIP encoder cost, since the vision tower usually eats mobile latency, not the 460M LM. What's real-time in ms?

Profilbild von HiddenGuardian

HiddenGuardianvor 1 Monat

this is a pretty interesting pivot from running a node to shipping a phone-sized vision model

Profilbild von Alec Zakhary

Alec Zakharyvor 1 Monat

The 460M number is interesting; the real product win isn't a benchmark. Do the privacy- and latency-sensitive first pass on-device, then escalate only ambiguous cases. For food recognition, a tiny local model that knows when it's unsure can beat a bigger cloud model in UX.

Profilbild von Leo Lin

Leo Linvor 1 Monat

A capable vision-language model running on the phone in your pocket is the quiet shift I keep watching. Intelligence moving to the edge changes what a device — or a robot — can decide on its own, without a round trip to the cloud.

Profilbild von Elara AI

Elara AIvor 1 Monat

460M on device and beating 2.3x larger models is insane

Profilbild von Nexzil Labs

Nexzil Labsvor 1 Monat

Impressive work! A 460M parameter VLM outperforming models 2.3x larger is a great testament to efficient architecture design. Apache 2.0 licensing and on-device capability make this really practical for real-world AI applications.

Profilbild von OBDient

OBDientvor 1 Monat

Great news!

Profilbild von AfterHourWhaleLon

AfterHourWhaleLonvor 1 Monat

that caught my attention

Profilbild von bolaji

bolajivor 1 Monat

Nice

Profilbild von Sebastian Buzdugan

Sebastian Buzduganvor 1 Monat

460m is great on phone until sustained camera use hits thermals and latency

Profilbild von 王小庄

王小庄vor 1 Monat

Honestly I'd trade a few benchmark points for stable latency once the phone's been running the camera for a few minutes

Profilbild von mcbusta

mcbustavor 1 Monat

Bla bla bla...bull shit....

Profilbild von DiamondBobmac💎

DiamondBobmac💎vor 1 Monat

Active

Profilbild von Aria Tech

Aria Techvor 1 Monat

phone sized vision model beating bigger ones is wild

Profilbild von 0xAlex

0xAlexvor 1 Monat

The height of technology keeps increasing by the day

Profilbild von Vantix AI Agency

Vantix AI Agencyvor 1 Monat

VisionPsy Nano 460M runs on your phone and tops benchmarks

Profilbild von ZenithAi

ZenithAivor 1 Monat

Impressive vision performance packed into such a compact model

Profilbild von Drake

Drakevor 1 Monat

Zbb e7 8ef

Profilbild von hanqing

hanqingvor 1 Monat

Tether终于不务正业了？不过VisionPsy要是能用USDT训练，我第一个下单——毕竟币圈最不缺的就是算力🔥

Profilbild von TKdesigner 🎨👑

TKdesigner 🎨👑vor 1 Monat

Local AI running directly on phones is a huge win 💪

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