# M5 Pro chip

Published articles for M5 Pro chip.

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## Running a 20B Video Diffusion Transformer on Consumer Hardware: A Deployment and Measurement Report for MiniMax H3 on Apple Silicon

DevFeed: [Running a 20B Video Diffusion Transformer on Consumer Hardware: A Deployment and Measurement Report for MiniMax H3 on Apple Silicon](<https://devfeed.tech/articles/running-a-20b-video-diffusion-transformer-on-consumer-hardware-a-deployment-and-measurement-report-for-minimax-h3-on-apple-silicon-113781.md>)

Original publisher: [Read original article](<https://arxiv.org/abs/2611.00843>)

Author: Luke Shi, Steven Shi

Published: 2026-11-03T05:00:00Z

Content type: article

Language: en

Sources: [arXiv: Distributed Computing](<https://devfeed.tech/sources/arxiv-distributed-computing.md>)

Topics: [diffusion-transformers](<https://devfeed.tech/topics/diffusion-transformers.md>), [MLX](<https://devfeed.tech/topics/mlx.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [ai evaluation](<https://devfeed.tech/topics/ai-evaluation.md>)

Tags: [17](<https://devfeed.tech/tags/17.md>), [abstract](<https://devfeed.tech/tags/abstract.md>), [apple-silicon](<https://devfeed.tech/tags/apple-silicon.md>), [clip](<https://devfeed.tech/tags/clip.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [consistency](<https://devfeed.tech/tags/consistency.md>), [cs-cv](<https://devfeed.tech/tags/cs-cv.md>), [cs-dc](<https://devfeed.tech/tags/cs-dc.md>), [data](<https://devfeed.tech/tags/data.md>), [dependency](<https://devfeed.tech/tags/dependency.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [diffusion](<https://devfeed.tech/tags/diffusion.md>), [generation](<https://devfeed.tech/tags/generation.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [human-review](<https://devfeed.tech/tags/human-review.md>), [innovation](<https://devfeed.tech/tags/innovation.md>), [latency](<https://devfeed.tech/tags/latency.md>), [m5-pro](<https://devfeed.tech/tags/m5-pro.md>), [m5-pro-chip](<https://devfeed.tech/tags/m5-pro-chip.md>), [measurement](<https://devfeed.tech/tags/measurement.md>), [minimax](<https://devfeed.tech/tags/minimax.md>), [video](<https://devfeed.tech/tags/video.md>)

### AI overview

The report demonstrates a local text-to-video pipeline for MiniMax H3, a 20.38B-parameter model, on an Apple Mac mini with an M5 Pro and 64 GiB of unified memory. The authors used the official bf16-to-Q8 quantization path on-device, without cloud services, and describe two deployment blockers and their fixes. A 15.08-second 576x1024 clip took 4,838.49 seconds to render, with 27.467 GiB peak MLX memory. In unattended use, the pipeline completed 17 clips over 26.49 hours with no render failures. Blind ratings of those clips averaged 3.12/5 for structural integrity, 3.18 for temporal consistency, and 2.94 for visible artifacts. These are the authors' measurements; the supplied excerpt does not include the deployment steps or results for all four resolution tiers.

### Source excerpt

arXiv:2611.00843v1 Announce Type: cross Abstract: We report the end-to-end deployment and measurement of MiniMax H3, a 20.38-billion-parameter video diffusion transformer (DiT) - the count measured from the safetensors headers of the Q8 checkpoint as deployed locally (Section 3.2) - running entirely on consumer Apple Silicon hardware: an Apple Mac mini with M5 Pro chip and 64 GiB of unified memory. Using the official bf16-to-Q8 (8-bit, group size 64) quantization path executed locally on the machine, we produced a working text-to-video pipeline with no cloud dependency. We document the full deployment procedure, including two non-trivial blockers and their fixes, and report measured figures for build time, peak memory, and per-clip render latency across four resolution tiers (Draft 384x640 through Native 768x1344). A 15.08-second 576x1024 clip rendered in 4838.49 seconds with a measured MLX peak of 27.467 GiB. We further operated the system as an unattended production pipeline, completing 17 clips in 26.49 hours with zero render failures. A blind human review of the 17 production clips (generation prompts withheld) averaged 3.12, 3.18, and 2.94 out of 5 for structural integrity, temporal consistency, and visible artifacts. All figures in this report are our own measurements except where explicitly labeled as third-party data. This is a systems/empirical report; we make no claim of model innovation.

## Apple launches new Mac Mini and Mac Studio models for on-device AI

DevFeed: [Apple launches new Mac Mini and Mac Studio models for on-device AI](<https://devfeed.tech/articles/apple-s-new-ai-ready-mac-minis-mac-studio-go-on-sale-today-here-s-what-to-know-58699.md>)

Original publisher: [Read original article](<https://indianexpress.com/article/technology/tech-news-technology/apples-ai-ready-mac-minis-mac-studio-on-sale-what-to-know-10890322/>)

Author: Tech Desk

Published: 2026-09-23T07:19:14Z

Content type: news

Language: en

Sources: [Technology | The Indian Express](<https://devfeed.tech/sources/technology-the-indian-express.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Mac Mini](<https://devfeed.tech/topics/mac-mini.md>), [On-device AI](<https://devfeed.tech/topics/on-device-ai.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [Computing](<https://devfeed.tech/topics/computing.md>), [idc](<https://devfeed.tech/topics/idc.md>), [Microsoft](<https://devfeed.tech/topics/microsoft.md>), [iphone](<https://devfeed.tech/topics/iphone.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [apple](<https://devfeed.tech/tags/apple.md>), [apple-intelligence](<https://devfeed.tech/tags/apple-intelligence.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [localized-ai-workloads](<https://devfeed.tech/tags/localized-ai-workloads.md>), [m5-max-chip](<https://devfeed.tech/tags/m5-max-chip.md>), [m5-pro-chip](<https://devfeed.tech/tags/m5-pro-chip.md>), [mac](<https://devfeed.tech/tags/mac.md>), [mac-mini](<https://devfeed.tech/tags/mac-mini.md>), [mac-mini-m6](<https://devfeed.tech/tags/mac-mini-m6.md>), [mac-studio](<https://devfeed.tech/tags/mac-studio.md>), [mac-studio-m5-ultra](<https://devfeed.tech/tags/mac-studio-m5-ultra.md>), [memory](<https://devfeed.tech/tags/memory.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [on-device-ai](<https://devfeed.tech/tags/on-device-ai.md>), [openclaw-ai-agent](<https://devfeed.tech/tags/openclaw-ai-agent.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rdma-over-thunderbolt](<https://devfeed.tech/tags/rdma-over-thunderbolt.md>), [tech](<https://devfeed.tech/tags/tech.md>), [technology](<https://devfeed.tech/tags/technology.md>), [technology-tech](<https://devfeed.tech/tags/technology-tech.md>), [unified-memory-architecture](<https://devfeed.tech/tags/unified-memory-architecture.md>)

### AI overview

Apple has released new Mac Mini and Mac Studio models designed to run AI workloads locally. The article discusses their chips, memory, networking, enterprise positioning, and potential use as an alternative to some cloud infrastructure.

### Source excerpt

Apple's new Mac Mini M6, Mac Mini M5 Pro, Mac Studio M5 Max, and Mac Studio M5 Ultra are now available, bringing faster performance and more memory for powerful on-device AI.