Expert guidance on choosing the right hardware AND models for local LLMs. Avoid £5k–20k mistakes in GPU selection, memory sizing, and picking models that actually fit your use case.
View Advisory ServicesThe Challenge
Most teams waste thousands on wrong configurations because benchmarks don't tell the whole story.
Mac Studio, NVIDIA GPUs, cloud credits. Wrong choices mean thousands burned and weeks of rework.
That 128k context model won't fit in 64GB RAM at production quality. Benchmarks rarely show real-world limits.
Many local models claim function calling but fail on real agent workflows. You won't know until you've committed.
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Three ways to get certainty before you invest.
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Ideal For
Technical leaders who need local inference but lack specialized ML infrastructure expertise.
28 Jan 2026 · Open Source Models
Chinese AI lab Moonshot AI has released Kimi K2.5, a massive 1 trillion parameter open source model.
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