💰 @MultiversX crossed $100M in market capitalization on October 27. It now stands at $105.2M, above the $100M the Mona Lisa was insured for in 1962. Holding some elrond-erd-2:native? Let us know in the replies 👇 📊

1,456x faster: MultiversX vs Bitcoin Max TPS ever recorded by Chainspect, side by side. One is a flood, the other is a drip. Who should we compare next? 👇 📊

Cardano still the third most developed blockchain network...? According to data from @chainspect_app, the @Cardano L1 has seen some 3,061 developer commits in the past 30 days. This figure is surpassed only by @Etheruem and @MultiversX, with figures of 8,187 and 6,807, respectively.

Algorand becoming one of crypto's most decentralised networks... According to data from @chainspect_app, @Algorand recently crossed the 1,550 validator milestone, adding a full 6 in just one day. At time of writing, its validator count stands at 1,545, making it the 4th largest network by validator count, behind only @ethereum, @MultiversX and @Cardano.

📢 𝗝𝗨𝗦𝗧 𝗜𝗡: Multiverse Computing Launches Comet 60B in collaboration with $NVDA NVIDIA 👉 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: ➤ 𝗠𝘂𝗹𝘁𝗶𝘃𝗲𝗿𝘀𝗲 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 launches 𝗖𝗼𝗺𝗲𝘁 𝟲𝟬𝗕, based on NVIDIA Nemotron 3.5 Super VL. ➤ Model size reduced 𝟱𝟬%, from 𝟭𝟮𝟬 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 to 𝟲𝟬 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 parameters. ➤ Retains 𝟭𝟮 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 active parameters and multimodal capabilities. ➤ Accuracy remains within 𝟱% of NVIDIA's original model across evaluated tasks. ➤ Comet 60B outperforms the original in selected 𝗔𝗜 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝘀. ➤ Supports 𝘁𝗲𝘅𝘁, 𝗶𝗺𝗮𝗴𝗲, 𝘃𝗶𝗱𝗲𝗼, and 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 workloads. ➤ Built using 𝗖𝗼𝗺𝗽𝗮𝗰𝘁𝗶𝗳𝗔𝗜 compression and reinforcement learning techniques. ➤ Available as an 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 model in 𝗕𝗙𝟭𝟲, 𝗙𝗣𝟴, and 𝗡𝗩𝗙𝗣𝟰 formats. ➤ Reduced model size enables lower 𝗚𝗣𝗨 𝗺𝗲𝗺𝗼𝗿𝘆 requirements and deployment costs. ➤ Multiverse previously launched 𝗣𝘂𝗹𝘀𝗮𝗿 𝟭𝟲𝗕 using NVIDIA Nemotron 3 Nano. 👉 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: ➤ 𝗟𝗼𝘄𝗲𝗿 𝗔𝗜 𝗖𝗼𝘀𝘁𝘀: Smaller models could reduce GPU infrastructure and inference expenses. ➤ 𝗚𝗿𝗲𝗮𝘁𝗲𝗿 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Preserves near-original performance while requiring substantially less model storage. ➤ 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻: Makes advanced multimodal AI more accessible to smaller organizations. ➤ 𝗔𝗜 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Could reduce memory requirements per deployment, improving hardware utilization. ➤ 𝗠𝗮𝗿𝗸𝗲𝘁 𝗜𝗺𝗽𝗮𝗰𝘁: Highlights growing competition around efficient AI models rather than parameter counts alone. 👉 𝗘𝘅𝗽𝗲𝗿𝘁 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁: 𝗘𝗻𝗿𝗶𝗾𝘂𝗲 𝗟𝗶𝘇𝗮𝘀𝗼, Co-founder and CEO of Multiverse Computing: “Agents need models that can read documents, understand images and follow video across long tasks, and they need to run where the data lives,” said Enrique Lizaso, co-founder and CEO of Multiverse Computing. “Nemotron 3.5 Super VL is an excellent multimodal model. With Comet 60B, we have cut its size in half while keeping accuracy within 5% of the original, so companies can run it on less hardware and at lower cost. That is exactly what our compression technology is built for.”