According to Soumith Chintala, a 10GW AI build equates to roughly $340B of Nvidia H100s at $30,000 per GPU, assuming 20% of power is reserved for non-GPU components (source: Soumith Chintala on X, Sep 23, 2025). He further estimates a 30% volume discount would reduce OpenAI’s outlay to about $230B (source: Soumith Chintala on X, Sep 23, 2025). Chintala contrasts the discounted scenario with a hypothetical where OpenAI pays full price and Nvidia reinvests the implied $100B delta into OpenAI equity, highlighting how deal structure could shift realized revenue versus strategic upside for NVDA (source: Soumith Chintala on X, Sep 23, 2025). For trading, the two price paths frame NVDA sensitivity to pricing power, gross margin mix, and potential strategic financing; if the 10GW plan referenced by OpenAI Newsroom on X guided actual orders, the magnitude implies a multi-hundred-billion-dollar pipeline that would be material for semis and AI-infrastructure equities while reinforcing AI-compute scarcity narratives that can influence crypto-adjacent GPU plays (sources: Soumith Chintala on X, Sep 23, 2025; OpenAI Newsroom on X as linked by Chintala).

According to @hyperbolic_labs, about 300 additional Nvidia H100 GPUs are now available on-demand at USD 1.49 per hour with instant spin-up, no calls or reservations, and rental scale from 1 to 136 GPUs via app.hyperbolic.ai, source: @hyperbolic_labs. This pricing and capacity disclosure provides a live benchmark for H100 compute costs that traders can use when evaluating AI-infrastructure narratives in crypto markets, source: @hyperbolic_labs.

According to @hyperbolic_labs, NVIDIA H100 GPUs are available today on Hyperbolic, with B200 and other next-gen accelerators to be added as supply stabilizes and once they meet internal reliability standards, source: @hyperbolic_labs, Aug 22, 2025. The company is sunsetting its Spot offering and providing a transition path to keep workloads running with enhanced reliability, source: @hyperbolic_labs, Aug 22, 2025. For traders tracking AI-compute exposure and crypto infrastructure that rents cloud GPUs, this confirms near-term hardware availability and a reliability-first policy on Hyperbolic that defines access conditions for AI and blockchain workloads on the platform, source: @hyperbolic_labs, Aug 22, 2025.

According to Hyperbolic (@hyperbolic_labs), LLoCO on NVIDIA H100 delivered up to 7.62x faster inference on 128k-token sequences and 11.52x higher throughput during finetuning, and enabled processing of 128k tokens on a single H100 (source: Hyperbolic on X, Aug 21, 2025). For trading context, these stated gains are concrete performance datapoints for assessing throughput per H100 in long-context LLM workloads and may inform evaluation of AI compute efficiency tied to H100 deployments (source: Hyperbolic on X, Aug 21, 2025).

According to Hyperbolic, LLoCO delivered up to 7.62x faster inference on 128k-token sequences on Nvidia H100 GPUs, based on their reported results; source: Hyperbolic @hyperbolic_labs, Aug 20, 2025. According to Hyperbolic, LLoCO achieved 11.52x higher throughput during finetuning on H100; source: Hyperbolic @hyperbolic_labs, Aug 20, 2025. According to Hyperbolic, LLoCO enabled processing of 128k tokens on a single H100; source: Hyperbolic @hyperbolic_labs, Aug 20, 2025.

According to @hyperbolic_labs, Nvidia's Hopper GPUs set the standard with FP8 mixed-precision and asynchronous pipelines, while the next-generation Blackwell series advances with FP4 precision, expanded memory, and NVLink-5 connectivity. The H100 GPU remains widely accessible for AI and crypto mining workloads, available for rent at $1.49 per hour. The new H200 and B200 GPUs offer improved performance and are available on request. This evolution in GPU technology is expected to enhance computational efficiency for AI-driven crypto trading and mining operations, potentially reducing costs and increasing throughput for algorithmic traders and blockchain infrastructure providers (source: @hyperbolic_labs).

According to @hyperbolic_labs, the latest performance comparison between NVIDIA H100 SXM, H200 SXM, and HGX B200 GPUs reveals significant upgrades in memory and bandwidth that could accelerate AI and crypto trading algorithms. The H100 SXM offers 80 GB at 3.35 TB/s with up to 3.96 PFLOPS (FP8), while the H200 SXM doubles memory to 141 GB and bandwidth to 4.8 TB/s, maintaining similar compute performance. The HGX B200 further increases capacity to 180 GB with 7.7 TB/s bandwidth and up to 9 PFLOPS (FP8). These advancements are expected to enhance high-frequency trading and decentralized AI-powered crypto strategies by enabling faster data processing and model training, which could influence demand for crypto-related GPU mining and AI infrastructure. Source: @hyperbolic_labs

According to @HyperbolicLabs, the launch of the first MCP server enables Claude by AnthropicAI to autonomously rent NVIDIA H100 GPUs, execute training scripts, and manage workloads using natural language commands (source: github.com/HyperbolicLabs/hy). This breakthrough increases efficiency and scalability for AI engineers, potentially accelerating AI-driven crypto trading bots and blockchain analytics tools. Enhanced access to high-performance GPUs may drive demand for related crypto tokens and infrastructure projects, especially those linked to decentralized compute and AI integration.