ProsGrow Engineering
Measured results from applying advances in AI models and serving systems to enterprise workloads—with clear performance, quality, and cost trade-offs.
MiniMax-H3 server inference fell from 19.392 to 8.913 seconds on the same eight GPUs. A separate Wan test cut warm latency by 59.1%.
Read post : How ProsGrow Improves MiniMax-H3 Video Inference Latency by 54%
Whisper benchmark throughput converts to about 7,200 source-audio hours per wall hour on eight GPUs, with 2.63% more throughput and a passing accuracy result.
Read post : How ProsGrow Reached 7,200 Audio Hours per Hour with Whisper
Qwen3 output throughput rose from 17,961 to 41,651 tokens/s on the same GPU. The 132% gain is measured against ProsGrow’s starting profile.
Read post : How ProsGrow Increased Qwen3 Batch Throughput by 132%
An eight-GPU benchmark reached 59,881 image variants/hour after a 32.5% single-GPU precision gain. Node profiling revealed where shared resources limited delivery.
Read post : How ProsGrow Reached 59,881 FLUX.2 Image Variants per Hour
Raw vector storage fell 75%, retaining 99.58% of baseline nDCG@10 on SciFact. A separate precision study raised embedding throughput by 69.10%.
Read post : How ProsGrow Cut Raw RAG Vector Storage by 75%
Document QA reached 45,978 questions/hour on the same eight GPUs. Profiling exposed hidden workload imbalance and recovered 3.07% more capacity.
Read post : How ProsGrow Reached 45,978 Document Questions per Hour
ProsGrow AI is building AI inference optimization infrastructure for production deployment, optimization, and GPU operations.
Read post : ProsGrow AI Expands AI Infrastructure and Inference Systems with Microsoft, Google Cloud, and AWS Startup Programs
ProsGrow AI is now a member of NVIDIA Inception as we build AI inference optimization infrastructure for deployment, optimization, and GPU operations.
Read post : ProsGrow AI Joins the NVIDIA Inception Program