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Local AI and GPU hardware2026-10-19· By Franz Senn

192 GB is orderable now: what the new boxes cost and what DeepSeek actually runs on them

On September 8 we compared three desktop boxes for local models and listed the successor to the Ryzen AI Max+ 395 as a spec sheet only: 192 GB instead of 128 GB, no price. Six weeks later several vendors name prices, one buyer has measured a machine, and an open benchmark series lists runs on the new chip. The calculation in our post on two DGX Spark running DeepSeek can now be held against third-party numbers.

Gorgon Halo is the codename of the Ryzen AI Max+ PRO 495, the successor to the Ryzen AI Max+ 395 ("Strix Halo"). The chip has 16 Zen 5 cores, 40 graphics units and an NPU rated up to 55 TOPS. It shares up to 192 GB of LPDDR5X-8533 between CPU and GPU, and AMD allows up to 160 GB of that for graphics.

What changed in the chip

AMD lists up to 192 GB for the 495, and the product page gives a 256-bit bus with LPDDR5X-8533. The page for the Ryzen AI Max+ 395 gives 256 bit, LPDDR5X-8000 and at most 128 GB. From those fields we calculate 273 against 256 GB/s, 6.7 percent more bandwidth. Framework also quotes 273 GB/s for the 495 and writes in its pre-order post that inference gets faster than on the first Desktop, without a figure.

For text generation, bandwidth mostly sets the speed. On the 395, lhl (llm-tracker.info) measured about 180 GB/s in decode, roughly 70 percent of nominal; we cited that in our comparison of September 8 and did not re-measure it. A 495 machine buys 50 percent more memory and 6.7 percent more speed on paper.

What the machines cost

The table shows list prices from vendors and retailers in the currency given, without shipping. We bought and measured none of these machines.

MachineBuildPriceAs ofSource
GMKtec EVO-X5 Pro, PRO 495192 GB + 2 TB6,249 euros (30 units), 6,399 early bird, 6,599 regular28.09.2026ComputerBase
ACEMAGIC F9A, PRO 495up to 192 GB (SSD size not stated by source)6,499 US dollars, pre-order30.09.2026Newsshooter
Framework Desktop DIY, PRO 495192 GBfrom 6,799 US dollars30.09.2026Phoronix
AMD Ryzen AI Halo, PRO 495192 GB + 2 TB7,299.99 US dollars12.10.2026VideoCardz
Minisforum MS-S1 MAX P495192 GB + 2 TB7,399 US dollars28.09.2026VideoCardz
GMKtec EVO-X2, Max+ 395128 GB3,799 euros08.09.2026our comparison

Two vendors can be compared across both generations. GMKtec wants 6,599 euros regular for the EVO-X5 Pro with 192 GB, where its 128 GB predecessor stood at 3,799 euros in our comparison: a 74 percent premium for 50 percent more memory, 34.37 against 29.68 euros per gigabyte, about 16 percent more. AMD walks the same path: according to VideoCardz 3,999.99 US dollars for 128 GB at the June launch and now 7,299.99 for 192 GB, 38.02 against 31.25 dollars per gigabyte. AMD's own blog pages state no price. The 30 units at 6,249 euros are not a price anyone can order again.

Orderable is the accurate word today. GMKtec's product page blocks automated requests; the shop's product feed listed the 192 GB variant with 2 TB as in stock on 5 November 2026, shipping within three business days. Minisforum UK lists the variant as sold out and states shipping in mid-November, Framework says shipments start in November, and ACEMAGIC named late October at pre-order (Newsshooter, 30.09.2026; we did not check whether that held). According to VideoCardz, AMD's Halo sits at several Micro Center stores as an in-store purchase (Linux version, in store only).

What actually runs on such a machine

One r/LocalLLM user ordered a Minisforum MS-S1 MAX P495 with 192 GB, installed Fedora 44 and measured over a weekend with llama.cpp (Vulkan, build 23f7aab). He raised the graphics memory window to 160 GiB. These are the claims of a single buyer, and we re-measured none of them. The Reddit page was not retrievable at our final check on 5 November 2026 (bot check); we give the figures as they stood in an earlier read of the post and could not re-read them. His generation speed at empty context across six models:

Generation speed on a 192 GB machine with a 495 chip, tokens per secondgpt-oss 120B MXFP458 · 58Qwen3.5 35B A3B Q6_K_XL53 · 53MiniMax-M2.7 230B IQ4_XS31 · 31Qwen3.8 Flash-Next Q4_K_XL28 · 28DeepSeek V4 Flash IQ3_S18 · 18Qwen3.8 27B dense Q6_K_XL9 · 9060
Third-party measurement, not ours and not re-readable by us (Reddit page unavailable on 2026-11-05): one machine, empty context, llama.cpp with Vulkan. The dense model is the slowest although its file is only 24 GiB. Without multi-token prediction. (Quelle: Reddit r/LocalLLM, weekend test on a Minisforum MS-S1 MAX P495)

According to the Reddit post, the file sizes carry the message: DeepSeek V4 Flash at 3 bits fills 108 GiB, MiniMax-M2.7 in IQ4_XS 101 GiB, Qwen3.8 Flash-Next in Q4_K_XL 104 GiB. At a 131k context DeepSeek took 108.9 GiB of the graphics window and MiniMax at 196k took 127.4 GiB, which is 68 and about 80 percent. At 32k context DeepSeek drops to 13 tokens per second, at 128k to 8. His verdict: he is sending the machine back, 8,000 dollars is not worth it. His figures come from short runs of 64 generated tokens on Vulkan rather than HIP, as he says himself.

The second source is the open series local-llm-benchmarks.dev, which publishes runs with a protocol. According to its database (retrieved 2026-11-05) it holds 10 single-machine runs on Gorgon Halo and one on two linked machines, next to 79 on Strix Halo. DeepSeek V4.1-Flash in Q2 reached 14.76 tokens per second on 30.09., MiMo-V2.6-Flash in MXFP4 18.27 on 23.09., and a 138 GB GLM-5.3-Flash mix 7.26 on 26.09. A later run of 24.10. with a different Q2 file (kyuz0, 1017-Q2) sits higher at 21.54, but with speculative decoding; we did not check the protocol behind it. A 138 GB file cannot load on any 128 GB machine, so the 192 GB decide what loads at all. On the chip's speed the series says little. GLM-5.3-Flash and DeepSeek V4.1-Flash have runs on both platforms, but on a single machine never with an identical file and identical software, so a clean 395-against-495 comparison cannot be derived from it.

Our own measurement next to it

On September 28 we served DeepSeek V4 Flash with 284 billion parameters across two DGX Spark with vLLM, in the original 159.6 GB build; the measurement is in our post on the Spark cluster. Of the 256 GB shared memory, 186 GB were usable in that build.

SetupFileSoftwareTokens per secondMeasured by, date
2x DGX Spark159.6 GB, originalvLLM63.7 (single user)us, 28.09.2026
Minisforum MS-S1 MAX P495108 GiB, IQ3_Sllama.cpp, Vulkan18 empty, 13 at 32k, 8 at 128kReddit user, post (date not verifiable by us)
Gorgon Halo machineQ2, antirezDwarfStar, ROCm14.76local-llm-benchmarks.dev, 30.09.2026

This is not a clean comparison: different file, different software, different chip. The direction is still clear. Our two-machine build was 3.5 to 4.9 times as fast as the single machine at 18 and 13 tokens per second, and it used the original file, which does not fit in 192 GB. On money: two DGX Spark cost 13,900 US dollars at the prices in our October post, so 218 dollars per token per second. Putting Framework's price of 6,799 dollars (per Phoronix) against the Reddit figures of the Minisforum machine gives 378 dollars per token per second in the best case (at 18) and 523 at 32k context (at 13); Framework itself measured nothing here. In our comparison of two cards per token, one RTX 5090 came to 51.05 euros per token per second on 16 October, with a 27B model and in a different currency.

The number the vendor promise fails on is the file size. AMD allows up to 160 GB, the files of DeepSeek V4 Flash add up to 159.62 GB on Hugging Face, the July 31 release (DeepSeek-V4-Flash-0731) to 166.89 GB. AMD does not say whether its 160 GB means gigabytes or gibibytes: in gigabytes, 0.4 GB is left for the KV cache and activations, in gibibytes about 12. In the Reddit test only the smaller IQ3_S file ran.

DeepSeek V4.1-Flash shows the same wall from the other side. The antirez Q2 file is 365.7 GB, 188.83 GiB of it Engram tables, which according to the model page DwarfStar reads row by row from disk instead of loading. That is how the model runs on a single machine at about 15 tokens per second, while it failed on memory in our Spark pair.

Network and chassis

All vendors fit the same chip, so the surroundings differ. On networking, per vendor specifications: AMD's Halo brings 10 GbE (per VideoCardz), GMKtec and Minisforum two 10 GbE ports each plus USB4 v2 at 80 Gbit. Framework lists 5 GbE and two USB4 ports, plus an AMD BIOS patch that lifts USB4 point-to-point links from 9 to about 30 Gbit. ACEMAGIC gives the F9A two 2.5 GbE ports and OCuLink. For a cluster of two machines, the only way our DeepSeek measurement ran, this line matters more than the percentage on the chip. To our knowledge nobody has measured whether a USB4 or 10 GbE pair of 495 machines gains speed.

What we do with this

We are buying nothing. For our workloads the price per delivered token counts, and our comparison put it at 51.05 euros per token per second on an RTX 5090. Two levers from the Reddit test (per the post, not re-read by us) have nothing to do with memory: multi-token prediction lifted the dense 27B model there from 9 to 24 tokens per second, and reusing the cached prompt cut the second turn from 35 to 164 seconds down to 1.2 to 4.4. We use multi-token prediction ourselves, for example in the card comparison above.

One question stays open: the same file with the same software on a 395 and a 495 would confirm or refute the 6.7 percent. If you need a large model in production and want to know whether one machine, a cluster or a card is enough, see our advice on running large models in-house; the other measurements in this series are in the topic hub Local AI and GPU hardware.

Status 5 November 2026: we re-checked this post against its sources. What changed: availability (Minisforum UK shipping mid-November, GMKtec in stock according to its product feed), several quotes and figures the sources did not support, the file sizes of DeepSeek V4.1-Flash, and the statement about the benchmark series: it holds runs of same-named models on both chips, just no comparable ones.

Further Reading

Questions?
Does DeepSeek V4 Flash fit on a 192 GB machine?+

The original weights (mixed FP4/FP8) barely, a more heavily quantised file comfortably. The files of DeepSeek V4 Flash add up to 159.62 GB on Hugging Face, the July 31 release to 166.89 GB. AMD quotes up to 160 GB as graphics memory without saying whether that means gigabytes or gibibytes: read as gigabytes, 0.4 GB is left, read as gibibytes about 12. According to his post (not retrievable for us lately), the Reddit tester loaded a 108 GiB IQ3_S file and reached 108.9 GiB of graphics memory in use at a 131k context.

Is a machine with the new 495 faster than one with the old 395?+

On paper by 6.7 percent, and nobody has measured it. Both chips sit on a 256-bit bus, only the memory clock rises from 8000 to 8533 MT/s. We know of no test that ran the same model with the same software on both chips, and in the local-llm-benchmarks.dev database (retrieved 2026-11-05) GLM-5.3-Flash and DeepSeek V4.1-Flash have runs on both platforms, but on a single machine never with the same file and the same software.

Would such a machine pay off for running models ourselves?+

For large models in daily use, not on today's numbers. The 495 machines start at 6,249 euros and, with DeepSeek V4 Flash, give 8 to 18 tokens per second depending on context according to the Reddit tester; large models in the open series sit at 7 to 18 without speculative decoding. Our RTX 5090 cost 6,790 euros in Austrian retail on 16 October 2026 and delivered 120 to 146 tokens per second with a 27B model. Those are different models, so the comparison shows only the order of magnitude.

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