Why 128K context dies on 16 GB
A model can advertise a 128K context window and still fail at 40K tokens on a 16 GB GPU. The architecture ceiling never promised that weights, KV cache, compute buffers, and the desktop compositor would fit on your card at the same time.
AI GPU comparison across three vendors
The AI hardware landscape has shifted significantly in 2026, with NVIDIA, AMD, and Intel all competing for developers who need GPUs capable of running local large language models and AI inference workloads.
MTP vs standard decoding on RTX 4080 — real benchmarks
I tested Speculative decoding (Multi-Token Prediction, MTP) performance in Qwen 3.6 27B and 35B on an RTX 4080 with 16 GB VRAM.
llama.cpp token speed on 16 GB VRAM (tables).
Here I am comparing speed of several LLMs running on GPU with 16GB of VRAM, and choosing the best one for self-hosting.
RTX 5090 in AU is scarce and overpriced
Australia has RTX 5090 stock. Barely. And if you find one, you will pay a premium that feels detached from reality.
Compose-first Ollama server with GPU and persistence.
Ollama works great on bare metal. It gets even more interesting when you treat it like a service: a stable endpoint, pinned versions, persistent storage, and a GPU that is either available or it is not.
LLM speed test on RTX 4080 with 16GB VRAM
Running large language models locally gives you privacy, offline capability, and zero API costs. This benchmark reveals exactly what one can expect from 14 popular LLMs on Ollama on an RTX 4080.
Choose the right terminal for your Linux workflow
One of the most essential tools for Linux users is the terminal emulator.
Real AUD pricing from Aussie retailers now
The NVIDIA DGX Spark (GB10 Grace Blackwell) is now available in Australia at major PC retailers with local stock. If you’ve been following the global DGX Spark pricing and availability, you’ll be interested to know that Australian pricing ranges from $6,249 to $7,999 AUD depending on storage configuration and retailer.
AI-suitable Consumer GPU' Prices - RTX 5080 and RTX 5090
Let’s compare prices for top-level consumer GPUs, that are suitable for LLMs in particular and AI in general. Specifically I’m looking at RTX-5080 and RTX-5090 prices.
Unify text, images, and audio in shared embedding spaces
Cross-modal embeddings represent a breakthrough in artificial intelligence, enabling understanding and reasoning across different data types within a unified representation space.
Deploy enterprise AI on budget hardware with open models
The democratization of AI is here. With open-source LLMs like Llama, Mistral, and Qwen now rivaling proprietary models, teams can build powerful AI infrastructure using consumer hardware - slashing costs while maintaining complete control over data privacy and deployment.
Configure context sizes in Docker Model Runner with workarounds
Configuring context sizes in Docker Model Runner is more complex than it should be.
AI model for augmenting images with text instructions
Black Forest Labs has released FLUX.1-Kontext-dev, an advanced image-to-image AI model that augments existing images using text instructions.
Enable GPU acceleration for Docker Model Runner with NVIDIA CUDA support
Docker Model Runner is Docker’s official tool for running AI models locally, but enabling NVidia GPU acceleration in Docker Model Runner requires specific configuration.
GPT-OSS 120b benchmarks on three AI platforms
I dug up some interesting performance tests of GPT-OSS 120b running on Ollama across three different platforms: NVIDIA DGX Spark, Mac Studio, and RTX 4080. The GPT-OSS 120b model from the Ollama library weighs in at 65GB, which means it doesn’t fit into the 16GB VRAM of an RTX 4080 (or the newer RTX 5080).
