Saw @Velvet_Capital’s release of Velvet Flash 0.1—it feels quite interesting.
Many people think that the bigger the AI, the stronger it is. But in scenarios like crypto trading, what truly matters may not be parameter scale, but whether you can get things right.
Velvet Flash 0.1 is a 4.0-billion-parameter model specifically built for crypto operations. It focuses on solving one problem: helping the AI understand, operate more steadily, and stay safer when dealing with actual fund transactions.
When ordinary large models face on-chain operations, they may make misunderstandings—for example, choosing the wrong command, misreading user intent, entering incorrect parameters, or even failing to warn users in time before high-risk actions.
By contrast, Velvet Flash’s design logic is more like that of a professional trading assistant:
First, understand your goal → choose the correct operation → verify the amount, tokens, network, and address → assess risk → confirm at key steps.
In crypto skills testing, Velvet Flash 0.1 ranked first with a score of 50, outperforming many models with larger parameter counts. Even more worth noting is that with only 4B parameters, it still demonstrates stronger execution ability in a dedicated setting.
This also points to a broader trend: AI doesn’t necessarily need to chase “universality.” Being sufficiently professional in a niche area can actually create greater value.
Especially in DeFi, wallets, and trading scenarios that involve asset security, speed and cost matter—but accuracy and risk control matter even more.
Velvet Flash 0.1 is just the beginning. Next, it will continue expanding support for more platforms and optimizing complex transaction flows, so that AI can truly become a reliable operations assistant for crypto users.
In the future, AI competition may not only be about who has the largest model, but about who can solve real problems in real scenarios. For Crypto, focusing on precision and safety may be more meaningful than simply piling on parameters.
Many people think that the bigger the AI, the stronger it is. But in scenarios like crypto trading, what truly matters may not be parameter scale, but whether you can get things right.
Velvet Flash 0.1 is a 4.0-billion-parameter model specifically built for crypto operations. It focuses on solving one problem: helping the AI understand, operate more steadily, and stay safer when dealing with actual fund transactions.
When ordinary large models face on-chain operations, they may make misunderstandings—for example, choosing the wrong command, misreading user intent, entering incorrect parameters, or even failing to warn users in time before high-risk actions.
By contrast, Velvet Flash’s design logic is more like that of a professional trading assistant:
First, understand your goal → choose the correct operation → verify the amount, tokens, network, and address → assess risk → confirm at key steps.
In crypto skills testing, Velvet Flash 0.1 ranked first with a score of 50, outperforming many models with larger parameter counts. Even more worth noting is that with only 4B parameters, it still demonstrates stronger execution ability in a dedicated setting.
This also points to a broader trend: AI doesn’t necessarily need to chase “universality.” Being sufficiently professional in a niche area can actually create greater value.
Especially in DeFi, wallets, and trading scenarios that involve asset security, speed and cost matter—but accuracy and risk control matter even more.
Velvet Flash 0.1 is just the beginning. Next, it will continue expanding support for more platforms and optimizing complex transaction flows, so that AI can truly become a reliable operations assistant for crypto users.
In the future, AI competition may not only be about who has the largest model, but about who can solve real problems in real scenarios. For Crypto, focusing on precision and safety may be more meaningful than simply piling on parameters.
