Verified65% confidenceFactExact time
GPT-4-level large language models have hundreds of billions of parameters and require billions of floating-point operations on high-end GPUs (such as NVIDIA A100/H100) for each response.
3
Sources
65%
Confidence
Long-term
Relevance
7/9/2026
First Seen
Sources
Microsoft 365 Price Hike of 42%: AI Feature Bundling and What Users Should Do
hackernewshackernews7/5/2026
Related Claims
UnverifiedEach inference requires loading model weights into GPU memory and generating responses token by token; GPT-4-level model parameter counts are typically on the order of hundreds of billions.84% similarVerifiedRepresentative large language models such as GPT-4, Claude, and Gemini typically have parameter counts in the hundreds of billions or more.79% similarVerified训练一次GPT-4级别的模型需要数万块A100/H100 GPU协同工作数月78% similarUnverifiedGPT-4.5 has a trillion-scale parameter count, meaning every forward pass demands enormous memory bandwidth and computational throughput.77% similar
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