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Tagged: gpu
RTX 5060 Ti 16 GB for Local AI: Measured LLM, Image and Speech Speeds
RTX 5060 Ti 16 GB tested for local AI: five LLMs from 42 to 116 tok/s, first-token times at 32K, image, video, 3D and speech speeds, and what to run on it.
6 min readWhy Dual RTX 3090s Hit 55 tok/s Instead of 220 with SGLang and DFlash2
A hands-on look at running Qwen3.8-27B on two 3090s with SGLang, and how PCIe x4 links, missing P2P, tight KV cache and power spikes crushed the advertised speed.
7 min readvLLM Serve Flags Explained, With Sensible Starting Values
A practical tour of the vllm serve flags you'll actually tune: dtype, memory use, context length, parallelism, API keys and quantization, with defaults to try.
4 min readLocal LLM Workstation: From 20 to 60 Tokens per Second with Two GPUs
A used Xeon box with two RTX 5060 Ti cards, Qwen 27B, tensor parallelism and NCCL: hardware rules, real speed gains, and a break-even calculation against API pricing.
9 min readFlashAttention and PagedAttention: Two Fixes for Two Different Bottlenecks
Learn how FlashAttention speeds up attention math through tiling and online softmax, how PagedAttention manages KV cache memory, and why vLLM-style stacks use both.
7 min readCerebras Wafer vs GPU for LLM Inference: A GPT-OSS Benchmark
Compare Cerebras' wafer-scale engine with GPU inference using GPT-OSS-120B across five workloads, then see how Ultrafast speeds up GPT-5.6 Sol through the API.
4 min readRunning Local Coding Models on a 12GB RTX 3060 With a Model Scheduler
How to pick models that fit a 12GB GPU and why switching between GGUF and SafeTensors backends behind one OpenAI-compatible endpoint turns into a scheduling problem.
5 min readQwen3.8-27B on One RTX 3090: 262K Context at 65-80 Tokens per Second
A recipe for running a dense 27B model with full context on a single 24 GB GPU: a tuned llama.cpp fork, a 14.5 GB quant, Turbo3 cache and MTP drafting.
8 min readQwen3.8-27B on One RTX 5090: vLLM, LACT Fan Control and Concurrency Benchmarks
Serve Qwen3.8-27B from a headless RTX 5090 with vLLM: Docker GPU setup, Prometheus and Grafana, fixing thermals with LACT, and where throughput saturates under load.
11 min read
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