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first_img On-chain investigation: Ascend associated addresses hold 3.2% of the MONTRA supply

On November 10, 2026, an on-chain investigation reported that the Elysium issuance platform Ascend associated address transferred approximately $140,000 through two privacy pools into three new wallets, and purchased shortly after MONTRA went live. The tokens were sent to the same FOMO wallet, which holds 32,014,541 tokens, accounting for about 3.2% of the supply, and this wallet has no purchase records. MONTRA is the platform token of the Elysium issuance platform Montra, which went live at 00:36 UTC on that day. Ascend co-founder is CryptoTomYT.Route A deposited 40,000 USDC into the Privacy Cash on Solana on November 10, and withdrew an equivalent amount 47 seconds later, exchanging it for 530.57 HYPE, then purchased 6,846,772 tokens and transferred them out. Route B deposited 100,328.25 USDC into the Base privacy pool on November 9 and withdrew an equivalent amount within the same hour. Two new wallets from Route B purchased approximately 25.6 million tokens within about 5 minutes of going live, with launch fees up to 23.2%.The investigation stated that Route A's deposit wallet previously received 27.7 SOL from ethanhates.sol and transferred approximately $66,200 to an address claimed by CryptoTomYT. The first funds for Route B came from an Arkham labeled FOMO account as analyzationz. The remaining 10 new wallets that transferred funds within the same hour, combined with the aforementioned buyers, hold a total of 25.8% of the LAUNCHPAD supply.

first_img Brian Hong joined the social trading application fomo, responsible for the Asia-Pacific region

Brian Hong announced that he has joined the social trading application fomo, responsible for the Asia-Pacific region. Brian Hong previously publicly identified as the head of growth for consumer blockchain Abstract in the Asia-Pacific region. He stated that many high-quality trading ideas around the world have never left the language in which they were originally written; traders in Seoul and New York can focus on the same asset for months but do not have access to each other's work. Both parties see the same prices, but the ideas behind the trades remain trapped in circles separated by language, local communities, and existing information flows.He wrote that for nearly a decade, he has been connecting products, services, and information between the East and West. Products are now easier to cross borders, but ideas are not; he feels this most acutely in the market, where some ideas with significant upside potential remain confined to a single language and community. He stated that fomo is the first product that makes him feel this situation can change, as it does not require consideration of chains or cross-chain bridges; it faces a single market where information flow shows what people are actually buying. A trade does not need translation; ideas from Seoul can reach New York on their own, with attribution remaining with the originator.Brian Hong expressed that this feeling has not faded, and he agrees with fomo's direction and development team, and will help grow a product he already uses daily. He referred to the Asia-Pacific as the most important region for this matter, but the Asia-Pacific is not a single location; the languages, cultures, and platforms differ. Most of what happens here exists in communities that are not visible to the outside world. Introducing users is only part of the work; a larger part is putting ideas that the world has yet to see onto the same map. He has opened private messages to traders, large players, creators, and chain builders in the region.

MiniMax officially open-sources the H3 raw image model, producing 16.8 million pixels in 6 steps

MiniMax officially released H3-Image and open-sourced the model weights. This model can directly generate images of 4096×4096, approximately 16.8 million pixels, without additional upscaling. According to official data, the generation time is less than 10 seconds, with speeds reaching up to 5 times that of mainstream products. Text-to-image and image editing have been integrated into the same model, supporting up to 16 reference images.H3-Image follows the architecture of the H3 video model, removing the audio component while retaining the original text encoder and redesigning the decoder for images. The core image generation network has 33.1 billion parameters, requiring only 6 sampling steps to generate an image. On August 7, MiniMax researcher Kiro revealed in a Reddit AMA that the team is developing a dedicated image model based on the H3 homogenous architecture and plans to open-source the weights. They also proposed a workflow where the image model generates the first frame, which is then handed over to H3 for video generation.On November 3, Pruna AI launched P-H3-Image based on the open-source H3 video model, supporting raw images and retouching, compressing the generation network from 33.1 billion to approximately 20 billion parameters, requiring only 8 sampling steps. The minimal quantization version is about 20 GB, with peak memory usage of approximately 21 GB when generating 8 million pixel images. The official MiniMax version retains the 33.1 billion parameter generation network, with a sampling step count of 6, and supports higher resolutions and more reference images, with the original weights plus the reused text encoder totaling approximately 135 GB. There are regional restrictions on the open-source license; the United States, United Kingdom, European Union, and South Korea are not within the community license authorization regions. Companies with annual revenues exceeding 1 million dollars or those providing model hosting services to third parties must obtain separate authorization in advance.
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