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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 görüntüleme • 1 ay önce •via X (Twitter)

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QVAC profil fotoğrafı

QVAC1 ay önce

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

adidshaft profil fotoğrafı

adidshaft1 ay önce

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

just soph profil fotoğrafı

just soph1 ay önce

wait can i run this on my iphone?

Ryan White profil fotoğrafı

Ryan White1 ay önce

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.

AI Mastery Guide profil fotoğrafı

AI Mastery Guide1 ay önce

460M beating models 2x its size is genuinely impressive

smiks profil fotoğrafı

smiks1 ay önce

@woxshter le goat

med halbaj profil fotoğrafı

med halbaj1 ay önce

Gibraltar est européenne mais Ceuta et Melilla sont africaine

sophs b. profil fotoğrafı

sophs b.1 ay önce

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

DeFiDave profil fotoğrafı

DeFiDave1 ay önce

Wow

Rompel profil fotoğrafı

Rompel1 ay önce

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?

HiddenGuardian profil fotoğrafı

HiddenGuardian1 ay önce

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

Alec Zakhary profil fotoğrafı

Alec Zakhary1 ay önce

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.

Leo Lin profil fotoğrafı

Leo Lin1 ay önce

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.

Elara AI profil fotoğrafı

Elara AI1 ay önce

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

Nexzil Labs profil fotoğrafı

Nexzil Labs1 ay önce

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.

OBDient profil fotoğrafı

OBDient1 ay önce

Great news!

AfterHourWhaleLon profil fotoğrafı

AfterHourWhaleLon1 ay önce

that caught my attention

bolaji profil fotoğrafı

bolaji1 ay önce

Nice

Sebastian Buzdugan profil fotoğrafı

Sebastian Buzdugan1 ay önce

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

王小庄 profil fotoğrafı

王小庄1 ay önce

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

mcbusta profil fotoğrafı

mcbusta1 ay önce

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

DiamondBobmac💎 profil fotoğrafı

DiamondBobmac💎1 ay önce

Active

Aria Tech profil fotoğrafı

Aria Tech1 ay önce

phone sized vision model beating bigger ones is wild

0xAlex profil fotoğrafı

0xAlex1 ay önce

The height of technology keeps increasing by the day

Vantix AI Agency profil fotoğrafı

Vantix AI Agency1 ay önce

VisionPsy Nano 460M runs on your phone and tops benchmarks

ZenithAi profil fotoğrafı

ZenithAi1 ay önce

Impressive vision performance packed into such a compact model

Drake profil fotoğrafı

Drake1 ay önce

Zbb e7 8ef

hanqing profil fotoğrafı

hanqing1 ay önce

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🔥

TKdesigner 🎨👑 profil fotoğrafı

TKdesigner 🎨👑1 ay önce

Local AI running directly on phones is a huge win 💪

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