{"slug": "beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-the", "title": "Beelink SER10 Max (Ryzen AI 9 HX 470): It “Caught” the M4 Pro — But Local-AI Buyers Should Read the Fine Print", "summary": "Beelink's SER10 Max mini PC, powered by AMD's Ryzen AI 9 HX 470 \"Gorgon Point\" chip, matches Apple's M4 Pro on a single TypeScript benchmark but falls flat elsewhere, with local LLM performance hampered by default CPU-only execution. The machine is a mid-cycle refresh of Strix Point, not the high-end Strix Halo, and buyers should expect limited AI capabilities without manual GPU configuration.", "body_md": "Alex Ziskind's latest video carries a headline that does its job: *\"AMD's Strix Successor Just Caught the M4 Pro.\"* And on one benchmark, it genuinely did. But the machine in the video — the **Beelink SER10 Max**, built on AMD's brand-new **Ryzen AI 9 HX 470 \"Gorgon Point\"** chip — is a more interesting and more *cautionary* buy than the title suggests, especially if you're shopping it to run local LLMs. We haven't tested one; what follows summarizes Ziskind's measured results and grounds them in primary specs and the wider local-AI picture.\n\n## First, the name games: this is Strix *Point's* successor, not Strix *Halo's*\n\nThis matters more than it sounds. The local-AI crowd has spent 2026 obsessing over **Strix Halo** — the Ryzen AI Max+ 395, with its 256-bit memory bus and up to 128 GB of unified memory. The chip in the [Beelink SER10 Max](https://www.amazon.com/dp/B0GSZ2SHB7?tag=57eqvt-20&ref=vettedconsumer.com) is not that. It's **Gorgon Point**, a mid-cycle refresh of the smaller **Strix Point** laptop platform. Per [AMD's own spec sheet](https://www.amd.com/en/products/processors/laptop/ryzen/ai-400-series/amd-ryzen-ai-9-hx-470.html?ref=vettedconsumer.com), the Ryzen AI 9 HX 470 is a **12-core part (4 Zen 5 + 8 Zen 5c)** boosting to ~5.2 GHz, paired with the same **Radeon 890M** iGPU (16 RDNA 3.5 compute units) and a **55-TOPS XDNA 2 NPU** that the year-old SER9 already had. [Independent coverage](https://www.club386.com/amd-ryzen-ai-9-hx-470-gorgon-point-apu-flex-muscles-with-12-cores-at-5-25ghz/?ref=vettedconsumer.com) confirms Gorgon Point is exactly that — a clock-and-polish refresh on Strix Point's bones, not a new architecture.\n\nSo set expectations accordingly: this is a capable thin-and-light-class mini PC, not a 70B-model machine. The SER10 Max ships with 32 or 64 GB (a 96 GB/2 TB config exists for around **$2,300**), and about half the memory can be carved out for the iGPU — Ziskind's 64 GB unit exposed ~29 GB as graphics memory.\n\n## The CPU story: one big leap, mostly flat, and a Geekbench number worth double-checking\n\nZiskind's developer suite tells a split-screen story. On the **V8 Web Tooling benchmark** (a real TypeScript/Babel/Terser toolchain), the SER10 jumped from the SER9's ~20 to **34.14** on the TypeScript score — a ~65% generational gain that lands it **within 5%** of both the base M4 and M4 Pro Mac minis (~35.99). That's the \"caught the Mac\" moment, and it's real.\n\nEverywhere else, it's flat. His all-core Python test: SER9 28.64s vs SER10 28.9s — a quarter-second apart, i.e. the same. His synthetic .NET compile: SER9 ~91s vs SER10 ~90.9s — again, identical. On the real-world **Umbraco** .NET build, the SER10 actually came in *slightly slower* (161s) than the SER9 (149s). None of that is a knock on the chip so much as physics: same iGPU, same core count, mild clock bump.\n\nOne number deserves a flag. The video's chart shows the M4 Pro at **~15,321** Geekbench 6 multi-core — and a sharp commenter (*@charlievarley*) caught that this looks like a **base-M4** score, not an M4 Pro one. They're right: [Geekbench's published Mac mini M4 Pro (14-core) average](https://browser.geekbench.com/macs/mac-mini-2024-14c-cpu?ref=vettedconsumer.com) is **~3,821 single / ~22,430 multi** across 5,000+ results. Using the correct figure, the multi-core gap between these mini PCs and the M4 Pro is *far* wider than the video's chart implied — the M4 Pro stays comfortably ahead on heavy compiles, which matches the Umbraco result. Worth knowing before you read \"caught the M4 Pro\" as a multi-core claim.\n\n## The local-LLM story: your AI runs on the wrong chip by default\n\nHere's the part that earns this box a place on a local-AI site. The SER10 has *three* things that can run a model — CPU, the Radeon 890M iGPU, and the XDNA 2 NPU — and out of the box on Windows, **Ollama uses the CPU**. Ziskind ran Qwen 2.5 7B and watched the CPU peg while the GPU and NPU sat idle, landing a sluggish **14.2 tok/s**. This isn't a one-off: AMD's own [GAIA bug tracker (issue #1295)](https://github.com/amd/gaia/issues/1295?ref=vettedconsumer.com) documents the same \"appears CPU-bound / not GPU-accelerated by default\" behavior on Strix-class parts.\n\nThe fix is a single environment flag. Setting `OLLAMA_VULKAN=true`\n\nmoves inference onto the iGPU via llama.cpp's [Vulkan backend](https://github.com/ggml-org/llama.cpp/discussions/10879?ref=vettedconsumer.com) — necessary because **ROCm still doesn't support these RDNA 3.5 iGPUs (gfx1150) on Windows**, so Vulkan is the real path. Flip it, and Ziskind's numbers jumped: Llama 3.2 3B went 27 → **37.5 tok/s**, Qwen 2.5 1.5B went 47.5 → **68.3 tok/s**. (If you want the click-by-click, this [Vulkan-for-Ollama walkthrough](https://www.binwh.com/en/2026/04/12/vulkan-ollama-amd-gpu/?ref=vettedconsumer.com) covers it.)\n\nThe NPU is the wildcard everyone asks about and nobody benchmarks. Using [AMD's Lemonade Server](https://developer.amd.com/playbooks/lemonade-getting-started/?ref=vettedconsumer.com) — an OpenAI-compatible local server that routes *prefill to the NPU and decode to the iGPU* — Ziskind got ~14.3 tok/s on a 1B model. The theory is sound: prefill (prompt processing) is compute-bound and the [NPU cuts time-to-first-token roughly in half](https://www.computeleap.com/blog/amd-lemonade-local-llm-server-guide-2026/?ref=vettedconsumer.com), while decode is memory-bound and better left to the GPU. In practice today it's promising plumbing, not a reason to buy.\n\n## The number that should drive your decision: memory bandwidth\n\nToken generation is **memory-bandwidth-bound** — every token requires reading the model's weights out of RAM — so for local LLMs, bandwidth predicts speed better than any CPU score. And this is where the \"successor\" gets awkward:\n\n**SER10 Max — DDR5-5600 (SODIMM, upgradeable): ~90 GB/s.** Ziskind notes Beelink moved to user-upgradeable DDR5 here.**SER9 — LPDDR5X-7500 (soldered): ~120 GB/s.** The*older*machine's memory is faster (per[Beelink's own SER9 spec](https://www.bee-link.com/blogs/all/ser9-performance-comparison-in-local-deployment-of-deepseek-r1-llm?ref=vettedconsumer.com)).**Strix Halo (Ryzen AI Max+ 395) — LPDDR5X-8000, 256-bit: ~256 GB/s.** Nearly 3× the SER10.\n\nRead that again: the new SER10 Max may trade *away* token-generation headroom versus the SER9 it replaces, because Beelink swapped fast soldered LPDDR5X for slower upgradeable DDR5. A commenter (*@taggerung890*) spotted it instantly — \"5600 vs 8000 on the 395 Max+.\" It's a real trade: you gain upgradeable, cheaper RAM and capacity; you give up the one spec that most governs LLM speed. For 7–14B models at Q4 that's fine. For anything bigger, the bandwidth wall — not the core count — is what you'll hit.\n\n## So which one should you actually buy?\n\nZiskind frames it as three machines, and that's the right framing:\n\n**Want a small, quiet dev box that also dabbles in local AI?** The SER10 Max is a fine pick — just budget the 10 minutes to enable Vulkan, and treat it as a 7–14B machine.**Value-shopping?** The[SER9](https://www.amazon.com/dp/B0DHNK7D1Z?tag=57eqvt-20&ref=vettedconsumer.com)is usually a couple hundred dollars cheaper, has the*same*890M iGPU, and — thanks to its faster soldered memory — may match or beat the SER10 at token generation. Used units turn up on[eBay](https://www.ebay.com/sch/i.html?_nkw=Beelink+SER9&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339155740&toolid=10001&mkevt=1&ref=vettedconsumer.com)too.**Doing serious CPU/compile work or living in macOS?** The[M4 Pro Mac mini](https://www.amazon.com/dp/B0DLBVHSLD?tag=57eqvt-20&ref=vettedconsumer.com)still leads single-core and IO-heavy builds, with a genuine ~22,400 multi-core — but a 1 TB / more-RAM config runs ~$2,000+ and Apple's memory pricing is brutal.**Actually buying this to run big local models?** Save for a real**Strix Halo** box. The r/LocalLLaMA consensus, as[aggregated buyer guides note](https://terminalbytes.com/best-mini-pc-for-local-llm-2026/?ref=vettedconsumer.com), has largely settled on the 128 GB Ryzen AI Max+ 395 minis — like the[GMKtec EVO-X2](https://www.awin1.com/cread.php?awinmid=45751&awinaffid=2937589&ued=https%3A%2F%2Fwww.gmktec.com%2Fproducts%2Famd-ryzen%25E2%2584%25A2-ai-max-395-evo-x2-ai-mini-pc%3Fvariant%3D46826048585882&ref=vettedconsumer.com)— for capacity-per-dollar. We cover those in our[Strix Halo vs DGX Spark](https://vettedconsumer.com/strix-halo-vs-dgx-spark-running-70b-locally-according-to-people-who-own-both/)and[Framework Desktop](https://vettedconsumer.com/framework-desktop-buyers-guide-the-repairable-strix-halo-box-that-runs-70b-models/)guides.\n\n## What viewers and owners are saying\n\nThe comment section under Ziskind's video skews skeptical — which, for a flat-ish refresh, is fair. The loudest themes:\n\n- Test real models, not toys:\n*\"benchmarks of models and context sizes that people are actually using… who's using a 7b model on one of these machines?\"*—*@mrhappy678 on YouTube*. (Reasonable; though 7–14B is genuinely what a 890M box is for.) - The bandwidth catch:\n*\"wait the ser10 doesn't use high speed RAM? 5600mt/s vs the 8000mt/s on the 395 max+?\"*—*@taggerung890 on YouTube*. - The Geekbench correction above, from\n*@charlievarley*. - \"I'd rather wait for the big one\":\n*\"Patiently waiting for the 495+ with 192GB RAM…\"*—*@TotusEius on YouTube*— i.e. the Strix Halo successor, again underscoring that this isn't that chip. - One genuinely useful pro-tip on the AMD/Vulkan path:\n*\"using Vulkan, you can combine dissimilar GPUs. I'm running a 16 gig RTX and a 16 GB Radeon, Gemma 31B, 128K context, entirely on GPUs.\"*—*@MichaelRainabbaRichardson on YouTube*.\n\nOn the price grumbling (*\"in 2024 I bought my GMKtec Ryzen 9 7940HS 32GB for $700; now something similar is $1,300\"* — *@Ahamshep*), they're not wrong — the 2025–26 memory crunch pushed this whole mini-PC class up, which is exactly why the SER9's value case is stronger than usual.\n\n## Sources & how we researched this\n\nWe have **not** tested a SER10 Max first-hand; this piece summarizes Alex Ziskind's [\"AMD's Strix Successor Just Caught the M4 Pro\"](https://www.youtube.com/watch?v=sxMSKyrnZH4&ref=vettedconsumer.com) (we skipped the sponsor segment) and cross-checks his findings against primary sources: [AMD's HX 470 spec page](https://www.amd.com/en/products/processors/laptop/ryzen/ai-400-series/amd-ryzen-ai-9-hx-470.html?ref=vettedconsumer.com) and [Gorgon Point coverage](https://www.club386.com/amd-ryzen-ai-9-hx-470-gorgon-point-apu-flex-muscles-with-12-cores-at-5-25ghz/?ref=vettedconsumer.com) for the chip; [Geekbench Browser](https://browser.geekbench.com/macs/mac-mini-2024-14c-cpu?ref=vettedconsumer.com) for the corrected M4 Pro scores; the [llama.cpp Vulkan discussion](https://github.com/ggml-org/llama.cpp/discussions/10879?ref=vettedconsumer.com) and [AMD GAIA issue #1295](https://github.com/amd/gaia/issues/1295?ref=vettedconsumer.com) for the \"CPU-by-default\" behavior; [AMD's Lemonade playbook](https://developer.amd.com/playbooks/lemonade-getting-started/?ref=vettedconsumer.com) for the NPU+iGPU hybrid path; and [Beelink's SER9 LLM notes](https://www.bee-link.com/blogs/all/ser9-performance-comparison-in-local-deployment-of-deepseek-r1-llm?ref=vettedconsumer.com) for the memory spec. Tokens/sec are Ziskind's measured figures; treat single-run numbers as directional, not gospel.\n\n## Related guides\n\n[Strix Halo vs DGX Spark: Running 70B Locally, According to People Who Own Both](https://vettedconsumer.com/strix-halo-vs-dgx-spark-running-70b-locally-according-to-people-who-own-both/)[Framework Desktop Buyer's Guide: The Repairable Strix Halo Box](https://vettedconsumer.com/framework-desktop-buyers-guide-the-repairable-strix-halo-box-that-runs-70b-models/)[Can I run it? — check which models fit your machine](https://vettedconsumer.com/can-i-run-it/)·[Quant picker](https://vettedconsumer.com/quant-picker/)\n\nBottom line: the SER10 Max is a solid little Windows dev box that, with one flag flipped, makes a perfectly good 7–14B local-AI machine. Just don't let the \"caught the M4 Pro\" headline talk you into it as a heavy-compile or big-model workhorse — on multi-core it isn't, and on the spec that matters most for LLM speed, memory bandwidth, it's a step behind both its own predecessor and the Strix Halo boxes the local-AI crowd actually reaches for.", "url": "https://wpnews.pro/news/beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-the", "canonical_source": "https://vettedconsumer.com/beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-should-read-the-fine-print/", "published_at": "2026-06-18 11:02:37+00:00", "updated_at": "2026-06-18 11:30:59.135201+00:00", "lang": "en", "topics": ["ai-research", "ai-products", "ai-tools", "artificial-intelligence", "large-language-models"], "entities": ["Beelink", "AMD", "Ryzen AI 9 HX 470", "Apple", "M4 Pro", "Ollama", "Alex Ziskind", "Radeon 890M"], "alternates": {"html": "https://wpnews.pro/news/beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-the", "markdown": "https://wpnews.pro/news/beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-the.md", "text": "https://wpnews.pro/news/beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-the.txt", "jsonld": "https://wpnews.pro/news/beelink-ser10-max-ryzen-ai-9-hx-470-it-caught-the-m4-pro-but-local-ai-buyers-the.jsonld"}}