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Dive into Hunyuan-A13B, our latest open-source LLM built on an MoE architecture for optimal resource efficiency and high performance. Watch the video to discover its core strengths and how it provides a robust foundation for advancement across academic research, cost-effective AI solution development, and innovative application exploration. Try it...

44,270 Aufrufe • vor 1 Jahr •via X (Twitter)

10 Kommentare

Profilbild von AshutoshShrivastava
AshutoshShrivastavavor 1 Jahr

Really good for it's size and similar other models.

Profilbild von cedric
cedricvor 1 Jahr

80B-A13B packs a punch! It’s a compact MoE that nails the balance between power and VRAM, plus it comes with 256k context. The benchmarks look great and go head-on with o1. This model is a gift for the community, and they even share benchmarks for the q8 and q4 quants.

Profilbild von Lasya Turiganti
Lasya Turigantivor 1 Jahr

@TencentHunyuan How can I use it in India ?

Profilbild von Aaliya
Aaliyavor 1 Jahr

Love this

Profilbild von 𝗭𝗲𝗻 𝗠𝗮𝗴𝗻𝗲𝘁𝘀
𝗭𝗲𝗻 𝗠𝗮𝗴𝗻𝗲𝘁𝘀vor 1 Jahr

Need compatibility with @lmstudio

Profilbild von Ai Lockup
Ai Lockupvor 1 Jahr

We are willing to showcase it on our YouTube Channel ! Please Inbox for details.

Profilbild von John E
John Evor 1 Jahr

Bro you guys are using an ai model to do your show case video, HIRE ME, I can run all English based publications and promos, and help you get a feel on English speaking vibe of your models and company, I will start for free

Profilbild von Prof Celso Fontes
Prof Celso Fontesvor 1 Jahr

Such a pity there is no western api provider yet for this model

Profilbild von Lasya Turiganti
Lasya Turigantivor 1 Jahr

@TencentHunyuan Can I get access to This High Power in India 🥺 🫂

Profilbild von Rediminds, Inc
Rediminds, Incvor 1 Jahr

A13B is a timely proof that smart sparsity > brute-force scale. 3 active experts per token gives you near-70B quality on a single 80 GB GPU—the price/perf envelope most startups need for on-prem deployments. Curious to see how the FP8 + expert routing tricks translate to longer-context fine-tunes.

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