Some testing on RTX Pro 4500 (With Oculink) on PrismaQuant, INT4 Autoround and NVFP4 W4A4 quantized model
Summary
Reports on testing the RTX Pro 4500 GPU with Oculink, focusing on INT4 Autoround and NVFP4 W4A4 quantized models using PrismaQuant.
Similar Articles
@superalesha: Don't dare bury RTX 3090 until you read this! @UnslothAI shipped two new 4-bit quants of qwen3.6-35b this week. i spent…
A benchmark comparison of nvfp4, nvfp4-fast, and AWQ 4-bit quantizations of Qwen3.6-35B on RTX 3090s shows similar performance, with the MTP head trick boosting throughput by 41%.
We quantized DeepSeek V4 0731 and benchmarked it against popular quants on 8× RTX 5090
The author quantizes DeepSeek V4 0731, fixing FP8 downconversion issues that skew baselines, and benchmarks 38 quant files on 8× RTX 5090 to show GPU-dependent results and file-size-based comparisons.
RTX Pro 4500 Blackwell Performance Numbers
A user shares performance benchmarks comparing the Nvidia RTX Pro 4500 Blackwell 32GB GPU against the RTX 5060 Ti 16GB for AI inference, showing 1.6-6x speed improvements depending on model size and quantization.
RTX Pro 4500 Blackwell - Qwen 3.6 27B?
A developer shares local inference benchmarks and systemd configurations for running the Qwen3.6-27B model on an NVIDIA RTX Pro 4500 Blackwell GPU using llama.cpp. The post requests optimization tips for throughput and explores potential use cases for larger models.
We quantized Qwen 3.8 27B and compared the quants on an RTX 6000
The team quantized Qwen 3.8 27B into various GGUF formats and benchmarked them on an RTX 6000, finding similar performance across quants with AD-Q6_K recommended for safety.