Recently, Velvet has another noteworthy update: @Velvet_Capital has officially launched its self-developed Velvet Flash 0.1. But what interests me the most this time is not 'another AI model has been released'. But instead: Velvet is not continuing to roll parameters, but is creating a small model specifically for serving Crypto. Velvet Flash only has 4 billion parameters, but it ranked first in the official Crypto Skills Benchmark with 50 points. As a comparison: Qwen3.5-27B：45 DeepSeek-V4：40 Llama-3.3-70B：32 Gemma-4-31B：31 Mistral-24B：20 A model with only 4B parameters actually surpasses a batch of general-purpose models with much larger parameter scales. I think the real interesting thing about this matter is not the title party of "4B wins 70B", but the product idea behind it. The AI required for Crypto trading may not require anything at all. What it really needs is: Can understand what the user really wants to do; Being able to choose the correct trading instructions; Can accurately identify tokens, amounts, chains, and addresses; Remind users when risks are discovered; When it comes to financial operations, know when to ask the user for confirmation. Especially the last point. In a normal chat scenario, if an AI answers a wrong sentence, it may just be awkward. But in Crypto, if AI interprets 1 ETH as 10 ETH or sends assets to the wrong chain, the result may be a real loss of funds. So I actually think: The most important indicator of financial AI should not be just whether it is smart or not, but whether it dares to stop in times of uncertainty. This is also something that Velvet Flash has drawn my attention to. In official testing, the untrained Base Model only scored 23 points, but after training for the Crypto scenario, Velvet Flash reached 50 points, more than doubling its overall performance. Among them, Safety increased from 28 to 61, Robustness increased from 26 to 53, and Clarity increased from 22 to 52. This indicates a very important issue: General AI ≠ Crypto AI. Crypto has its own trading logic, chain, assets, protocols, and risks. A truly useful model for trading does not require understanding "all the knowledge in the world", but rather how to make correct, controllable, and secure operations in specific financial scenarios. The 4B model also has a practical advantage: Lower deployment costs, lower latency, and stronger autonomous control capabilities. Velvet Flash currently runs on Velvet's own infrastructure, which means they can continuously train, iterate, and optimize around their own product rather than relying entirely on an external generic model. So in my opinion, what Velvet really deserves attention this time is not the release of an AI model. But rather, they are trying to establish their own Crypto AI capability stack. If AI truly enters the trading scene in the future, I believe competition will not only be limited to: Whose model parameters are the largest. But rather: Who understands Crypto better, who is faster, who is cheaper, and who can be secure enough when it comes to funds. Velvet Flash 0.1 is only the first version. But I think this direction is worth continuing to observe. @Velvet_Capital