Models & benchmarks
28 articles
A new frontier model lands most weeks and almost every launch claims a benchmark win. These articles audit those claims: what a model costs per million tokens, where it fails, how open weights compare to hosted APIs, and which numbers matter once a model is inside a workflow. Comparisons are run on hardware we own, and the method is always stated.
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Showing 21 to 28 of 28
The Week Open-Source AI Went Nuclear: 25+ Open-Weight Drops That Changed Everything
25+ frontier open-weight AI models dropped in one week across every modality. The full breakdown of the most insane week in open-source AI history.
How We Optimised a 229 Billion Parameter AI Model on a Desktop Computer: A 12-Phase Journey
We deployed MiniMax M2.7 (229B params) on a single NVIDIA DGX Spark and spent a day optimising it. Thread tuning added 12% speed, --no-mmap cut cold start from 8 min to 90 seconds, and we discovered a GCC bug on Grace CPU. Full breakdown of what worked and what did not.
We Hit 120 Tokens Per Second With 1 Million Token Context on a Single Desktop AI Computer
How we achieved 120 tok/s with 1 million token context on a single NVIDIA DGX Spark using Atlas and Qwen 3.6 NVFP4. Zero regression, 100% retrieval accuracy, zero per-token cost.
Why We Run Two AI Models on Two Desktop Computers Instead of One Big One
How a two-model private AI cluster using Qwen 3.6 (120 tok/s) for speed and Step 3.5 Flash (20.6 tok/s) for reasoning outperforms a single-model setup. Built on two NVIDIA DGX Sparks for $18K AUD with zero ongoing costs.
DeepSeek V4 vs GPT-5.5 vs Claude Opus vs GLM: Cost and Benchmark Comparison for AI Agent Fleets
DeepSeek V4, GPT-5.5, Claude Opus, and GLM compared on cost, benchmarks, and self-hosting viability for autonomous AI agent fleets.
The Best Chinese AI Model for OpenClaw: GLM-5 vs Kimi K2.5 vs MiniMax M2.5
Comprehensive comparison of GLM-5, Kimi K2.5, and MiniMax M2.5 for OpenClaw autonomous agents. MiniMax M2.5 delivers 80.2% SWE-Bench performance at 62% lower cost than competitors.
Why AI Benchmarks Don't Matter (And What to Look at Instead)
AI benchmarks measure narrow tasks, not whether a tool helps your business. What to look at instead: cost, reliability, integration and Australian data rules.
ChatGPT vs DeepSeek vs Claude vs Gemini: Which AI Should Australian Businesses Actually Use in 2026?
ChatGPT vs DeepSeek vs Claude vs Gemini: Which AI Should Australian Businesses Actually Use in 2026?
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