Alpaca Network

This account is verified. Learn more

@AlpacaNetworkAI

🦙 Building Modelz, the first DEX that turns AI models into liquid, tradeable tokens and streams API revenue back to holders. t.me/alpacanetworkai

ERC-20 & Cross-chain modelz.io Joined July 2024

713 Following 13K Followers 12K Posts

Latest posts 5

Pinned post

Alpaca Network @AlpacaNetworkAI Oct 24, 2025

Every week a new model drops.

New APIs. New keys. New rate limits.
More chaos for developers.

Gatewayz fixes it.
One API for 10,000+ models.
One line of code away.

0:33

Alpaca Network @AlpacaNetworkAI Sep 22

Open AI needs people who can afford to keep maintaining it.

Hugging Face bringing oMLX's creator on board gives that work sustained backing while the project stays Apache 2.0.

Funding the work after launch deserves as much attention as launch day.

Pedro Cuenca Verified account @pcuenq Sep 22

Super happy to welcome @jundotkim, oMLX creator, to Hugging Face! 🥳

We are invested in Local AI and support MLX since @awnihannun and @angeloskath released it in Christmas 2023.

oMLX gets stability and speed. It remains a community project led by Jun.

huggingface.co/blog/omlx
View quoted post on X

Alpaca Network @AlpacaNetworkAI Sep 21

Tokenized finance got a new settlement connection today.

The Eurosystem launched Pontes, allowing eligible institutions to settle wholesale tokenized-asset transactions in central bank money.

The cash side of the trade is getting an upgrade.

Alpaca Network @AlpacaNetworkAI Sep 19

Jev reached nearly 13% of paid teams on Vercel AI Gateway in its first day, according to Vercel.

That's a reason to watch specialized models closely.

The next signal I'd want: how many teams keep using it a month later.

Vercel @vercel Sep 18

Jev was adopted faster than any other model in AI Gateway history.

In the first day, @typesafeai reached ~13% of teams, 2x the GPT-5.6 family and 6x Fable 5.1.

View quoted post on X

Alpaca Network @AlpacaNetworkAI Sep 18

Open models become more useful when more people can afford to run them.

Releasing the optimization code matters: other teams can inspect it, test it, and build on the work.

Lower compute barriers give more researchers room to experiment.

Anthropic Verified account @AnthropicAI Sep 17

Biologists use specialized open-source models for tasks like modeling the structure of molecular systems, designing drug-like molecules, and predicting the effects of genetic mutations. But these models are often expensive to run, potentially limiting their impact.

In our latest Science Blog, we share how Claude was able to optimize inference for more than 30 open-source models, making them 4x faster on average, partly by writing custom software for GPUs. We’re open sourcing all of the optimization code.

Read more: anthropic.com/research/claud…

View quoted post on X