AMD Strix Halo vs Apple M5 Max: The 128GB Unified Memory Local AI Showdown

If you want to run big AI models locally without buying several expensive GPUs, two platforms offer up to 128GB of fast unified memory in a small box: AMD’s Ryzen AI Max+ 395 (“Strix Halo”) and Apple’s M5 Max, in the 2026 Mac Studio and the MacBook Pro. Both can hold 70B-class models and ~120B Mixture-of-Experts models that won’t fit on a consumer GPU. This guide compares them on what matters for local LLMs: how much memory the GPU can actually use, how fast each one generates text, how fast it reads a long prompt, software, and cost.

Key Takeaways

• Capacity is a tie. Both expose about 96GB to the GPU by default, so in our model database both hold the same 28 of 30 models at 4-bit. Only the two DeepSeek giants (V3 671B and V4-Flash) fit on neither.
• Apple generates text about 2.4× faster. The M5 Max has up to 614GB/s of memory bandwidth against Strix Halo’s 256GB/s, and token generation scales with bandwidth.
• The model you pick moves speed more than the machine. On Strix Halo, Qwen3.6 35B-A3B is estimated at ~92.4 tokens/sec and Llama 3.3 70B at ~4.2: a 22× gap, against 2.4× between the two chips.
• Strix Halo is the cheaper route to 128GB and runs Windows or Linux. The M5 Max is faster and needs less setup.

Specs Compared

How much memory the GPU can actually use

“128GB” is the system total, not what the GPU gets. AMD says that of up to 128GB, “up to 96GB can be converted to VRAM through AMD Variable Graphics Memory” on Windows; Linux users commonly allocate more. On the Mac, macOS caps how much unified memory the GPU may wire by default, and the cap can be raised with iogpu.wired_limit_mb, which our Mac VRAM Optimizer generates for you.

Our hardware database treats both machines as 96GB GPU-usable, which is why their fit lists come out identical: 28 of the 30 models we track load at 4-bit on each. If you raise either limit, both gain the same headroom. Capacity does not separate these two machines; bandwidth does.

Estimated speed, model by model

Text generation reads the model’s active weights once per token, so speed is roughly memory bandwidth × 0.65 ÷ active weights in GB. These are the same figures our Strix Halo and M5 Max device pages print, computed from published specs. They are estimates, not our own measurements; our tokens-per-second guide explains the formula and where it runs high.

Dense models (every parameter read for every token)

Mixture-of-Experts models (only the active experts are read)

MoE figures are theoretical upper bounds. Routing overhead and expert loading make real results lower, sometimes by a lot.

The pattern matters more than any single number. On Strix Halo a dense 70B model is estimated at ~4.2 tokens/sec, which is slow for chat. But gpt-oss-120b, a larger model by total size, reads only 5.1B active parameters per token and is estimated at ~58.6. On Strix Halo, MoE models are the sweet spot; on the M5 Max, dense models up to 70B are practical too.

Prompt processing is the other half

Everything above is generation speed, which bandwidth sets. Reading a long prompt (a document, a codebase, a long chat history) is compute-bound instead, and that is where Apple has put its new hardware. Apple says the M5 Max delivers “Up to 10.7x faster LLM prompt processing in LM Studio when compared to Mac Studio with M1 Max, and 3.9x faster than M4 Max.” That is Apple’s own figure, not an independent one.

There is no like-for-like published comparison of prompt processing between these two chips. AMD’s own LM Studio benchmark compares Strix Halo against an Intel laptop chip, not against Apple. So treat this as a known unknown: if your work is mostly long-context reading (RAG, summarising, code review), the M5 Max’s accelerators are a plausible advantage, but no one has published numbers that settle it. Our context window guide covers the memory side of long prompts.

Software Support

Apple: mature and easy. Ollama and LM Studio (llama.cpp and MLX) use the GPU through Metal. See our Mac VRAM Optimizer to raise the default GPU memory limit.

Strix Halo: works well with llama.cpp-based tools through Vulkan or ROCm, and LM Studio supports it. On Windows, AMD’s Variable Graphics Memory setting controls how much RAM the GPU can use (up to 96GB). Linux users often configure larger GPU allocations. Expect a little more setup than on a Mac.

AMD’s refresh is available to pre-order: the Ryzen AI Max+ PRO 495

AMD has released a refresh of Strix Halo. Its spec page for the Ryzen AI Max+ PRO 495 lists the same 16 Zen 5 cores and 40 RDNA 3.5 compute units, with memory raised to 192GB and its speed to 8533MT/s, for 273GB/s of bandwidth. Framework takes pre-orders for its Desktop with this chip in a 192GB configuration at $6,799 before storage, with its second batch due to ship in November (checked 12 October 2026).

For this comparison that changes two things. Bandwidth rises about 7% over the 395, so the M5 Max’s lead in generation speed narrows only slightly, from about 2.4× to about 2.2×. But 192GB lifts AMD’s capacity ceiling above the M5 Max’s 128GB, enough for a 4-bit build of GLM-5.3-Flash. A genuinely new generation is further out: a February 2026 report from HWCooling said the Zen 6 successor is not expected until 2028, and a leak covered by Tom’s Hardware says it could move to LPDDR6. AMD has confirmed neither.

Which Should You Buy?

• Choose Strix Halo for the lowest-cost route to 128GB, if you mainly run MoE models (gpt-oss-120b, Qwen3.6-35B-A3B, Llama 4 Scout) or want Windows or Linux. If you need more than 128GB, the PRO 495 goes to 192GB.
• Choose an M5 Max if you want faster generation for dense 27–70B models, likely faster prompt processing, the smoothest software experience and quiet operation, and the higher price works for you. The Mac Studio M5 Max starts at $2,499 in the US; with the 40-core GPU and 128GB it lists at $5,099 (AppleInsider’s price guide, 11 October 2026). For comparison, Framework lists its Desktop with the Ryzen AI Max+ 395 and 128GB at $3,449 before storage (12 October 2026).

Need more than 128GB? The Mac Studio M5 Ultra goes up to 512GB with 1.2TB/s. See our giant-model sizing guide. To compare the two machines side by side on every spec, use our M5 Max vs Strix Halo comparison tool. Weighing NVIDIA’s 128GB box instead? See DGX Spark vs Strix Halo. Also see best Mac for local LLMs, how much RAM and VRAM you need, and the VRAM Calculator.

FAQ

Is Strix Halo or the M5 Max better for local AI?

For speed, the M5 Max: about 2.4× the memory bandwidth, so roughly 2.4× the text-generation speed on the same model, plus Apple’s claimed prompt-processing gains. For price and operating-system choice, Strix Halo. Both hold the same models.

Can Strix Halo run a 70B model?

Yes. It fits in 128GB at 4-bit, but expect only about 4 tokens per second because of the 256GB/s memory bandwidth. A Mixture-of-Experts model such as gpt-oss-120b will feel much faster, and so will Qwen3.8-Flash-Next in a 90–94GB build.

Is the M4 Max still a good buy?

If discounted, yes. Its up to 546GB/s of bandwidth is close to the M5 Max for text generation, although Apple says the M5 Max processes prompts up to 3.9× faster.

Sources

• AMD: Ryzen AI Max+ 395 (cores, compute units, Variable Graphics Memory)
• AMD: Ryzen AI Max+ PRO 495 (192GB, 8533MT/s, 273GB/s)
• Apple: Mac Studio with M5 Max and M5 Ultra (cores, bandwidth, price, prompt-processing claim)
• gpt-oss-120b model card
• Model sizes and speed estimates: BFWR hardware and model database, the same data as the hardware matrix

Prices for 128GB configurations and the PRO 495’s availability added 12 October 2026. Updated 10 October 2026: model-by-model estimates computed from our hardware database, sections on GPU-usable memory, prompt processing and AMD’s Ryzen AI Max+ PRO 495 refresh added, and specs re-checked against AMD’s and Apple’s pages. Every speed figure is an estimate from published specs; BFWR does not run its own benchmarks.