GPU & AI infrastructure
Best GPU for LLM inference: matching H100, H200 and L40S to model size
Which GPU to use for LLM inference by model size, precision, context length and concurrency — a sizing guide for Qwen, Llama, DeepSeek and MiniMax.
Research
GPU & AI infrastructure research
Research articles on gpu & ai infrastructure: sourced analysis, comparison tables, methodology and limitations.
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GPU & AI infrastructure
Multi-user LLM inference: how concurrency, context and KV cache limit a GPU
How many concurrent users a GPU can serve: KV-cache capacity by context length, why latency rises with load, and how to benchmark concurrency properly.
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GPU & AI infrastructure
NVIDIA H100 vs H200 for LLM inference: memory, bandwidth and when the upgrade matters
H100 vs H200 compared on specifications, model fit, KV-cache headroom and decode bandwidth ceilings for Llama, Qwen and DeepSeek inference.
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GPU & AI infrastructure
NVIDIA H100 vs L40S: which GPU fits your inference workload?
H100 vs L40S compared on memory, bandwidth, FP8 compute and model fit, with derived decode ceilings and published cloud prices per GPU-hour.
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GPU & AI infrastructure
NVIDIA H200 vs L40S: capacity, bandwidth and inference cost trade-offs
H200 vs L40S compared for LLM inference: 141 GB HBM3e vs 48 GB GDDR6, decode ceilings, model fit from 7B to 72B and published cloud prices.