According to @hyperbolic_labs, Hyperbolic is set to launch its Business & Enterprise Cloud featuring 99.9% uptime and H100 GPUs at prices 70% lower than competitors. This development allows teams to train three times more AI models and deploy in minutes, giving a significant cost and speed advantage for AI-driven crypto trading strategies. The first 100 teams will secure locked-in launch pricing, which could accelerate AI model deployment in the cryptocurrency sector and enhance algorithmic trading competitiveness (Source: @hyperbolic_labs, June 2, 2025).

According to Hyperbolic Labs on Twitter, the company is now offering on-demand H100 GPUs at a competitive rate of $0.99 per hour, with options for both SMB and enterprise clients to secure reserved deals, 99.9% uptime, and savings of up to 70% compared to legacy cloud providers (source: Hyperbolic Labs, Twitter, May 28, 2025). This significant reduction in GPU costs is expected to accelerate AI model development and deployment, which can drive increased demand for crypto tokens related to AI and decentralized compute infrastructure, such as Render (RNDR) and Akash Network (AKT). Traders should monitor related cryptocurrencies for heightened volatility and potential upside, as more affordable GPU access could spur growth in blockchain-based AI solutions.

According to @theamrelhady on Twitter, Hyperbolic's compute marketplace now features H100 GPUs starting at just $0.99 per hour, providing cost-effective access for AI model training and crypto mining (source: twitter.com/theamrelhady). This competitive pricing can lower operational costs for traders leveraging GPU acceleration for crypto algorithmic trading, mining, or machine-learning-driven market analysis. The platform's transparent pricing allows users to compare and select the most affordable compute resources, supporting profit optimization strategies in the volatile crypto market.

According to Jeff Dean, the release of Gemma 3, an open source model with 27B parameters, marks a significant advancement. It is multimodal, efficiently fits in a single H100 GPU, and performs exceptionally well on TPUs, indicating potential for broad application in AI-driven trading algorithms.

According to Sundar Pichai, Gemma 3 introduces groundbreaking efficiency in AI models, with its largest 27B model operating on just one H100 GPU. This represents a significant leap, requiring at least 10 times less computational power for similar performance compared to other models, potentially reducing operational costs and energy consumption for traders and developers.