Google's TurboQuant Cuts LLM Memory 6x With Zero Loss
Google Research's TurboQuant compresses LLM key-value cache by 6x and delivers 8x speedup on H100 GPUs with zero accuracy loss - no fine-tuning required.
Articles Tagged "Quantization"
NVIDIA Rubin CPX - Inference GPU With GDDR7
Full specs, benchmarks, and analysis of the NVIDIA Rubin CPX - a purpose-built inference GPU with 128GB GDDR7, 30 PFLOPS NVFP4, and 3x faster attention versus Blackwell, targeting million-token context workloads.
NVIDIA Rubin R200 - Next-Gen AI Superchip
Complete specs, benchmarks, and analysis of the NVIDIA Rubin R200 GPU - the post-Blackwell flagship with 288GB HBM4, 22 TB/s bandwidth, and 50 PFLOPS FP4.
NVIDIA B200 - Blackwell Flagship GPU
Complete specs, benchmarks, and analysis of the NVIDIA B200 - the Blackwell-architecture flagship GPU with 192GB HBM3e, 8 TB/s bandwidth, and up to 9,000 TFLOPS FP8.
NVIDIA H100 SXM - The AI Training Benchmark
Complete specs, benchmarks, and analysis of the NVIDIA H100 SXM - the Hopper-architecture GPU that defined the standard for AI training and inference performance.
NVIDIA H200 - Inference-Optimized Hopper
Complete specs, benchmarks, and analysis of the NVIDIA H200 - the HBM3e-equipped Hopper GPU that delivers 76% more memory and 43% more bandwidth than the H100 for inference workloads.
Qwen 3.5 FP8 Weights Drop - How to Actually Deploy a 397B Model on 8 GPUs
Alibaba releases official FP8-quantized weights for the Qwen 3.5 flagship and 27B dense model, cutting memory requirements roughly in half and enabling deployment on 8x H100 GPUs with native vLLM and SGLang support.
