Apple launches M6 and M5 Ultra, delivering a major boost in performance and AI computing
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| Source: Mastodon | Original article
Apple unveiled its M6 and M5 Ultra chips, promising a major boost in performance and on‑device AI compute with expanded unified memory for running large models locally.
Apple unveiled two next‑generation Apple Silicon chips on Tuesday, positioning the company for a decisive push into on‑device artificial‑intelligence. The M6, built on a 2 nm process, powers a refreshed Mac mini, while the M5 Ultra – a quad‑die processor – equips the new Mac Studio as its most powerful chip to date. Both chips are marketed with “ridiculous” amounts of unified memory – configurations start at 256 GB and a 512 GB option is slated for October – and are billed as capable of running large language models locally without relying on cloud services.
The launch marks a clear response to the narrative that Apple lags behind rivals in AI. By integrating massive memory and dedicated AI compute into its desktop line, Apple aims to let developers download and run models directly on the hardware, echoing the on‑device focus we highlighted in our coverage of Apple’s AI‑centric desktops on 26 August. The M5 Ultra‑equipped Mac Studio can be configured with 256 GB of RAM, 16 TB of storage and a price tag of $18,299, underscoring Apple’s premium positioning in the high‑end workstation market.
Why it matters is twofold: first, the chips promise a substantial performance uplift for professional workloads such as video rendering, scientific simulation and AI research; second, they signal Apple’s intent to keep AI processing in‑house, potentially reducing dependence on external cloud APIs and differentiating its ecosystem from competitors like Nvidia’s edge AI offerings.
What to watch next includes the October rollout of the 512 GB memory variant, early benchmark results that will reveal real‑world AI throughput, and how quickly developers adopt Apple’s tools to compile and optimise models for the new silicon. The rollout will also test whether Apple can translate its hardware advantage into a broader AI software ecosystem.
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