Best Local LLM for 512GB RAM (2026): GLM-5.3 at 4-Bit
Apple opened the 512GB Mac Studio M5 Ultra for order on 28 October 2026, at $22,299. It is the first machine you can buy new that holds a 750B-class model at 4-bit in one box. We read every file size below from the Hugging Face API on 1 November 2026. The short answer: GLM-5.3 at 4-bit is the largest model that fits at 4-bit or better, MiniMax M3 is the one that fits at 8-bit, and you must raise one macOS limit before either loads.
Bottom Line
- Best pick: GLM-5.3 at 4-bit. The UD-Q4_K_XL GGUF is 435.2 GiB. It is the largest open model that fits 512GB at 4-bit or better.
- Best 8-bit pick: MiniMax M3 at Q8_0 (422.5 GiB). Near-lossless quality from a smaller model.
- 1T-class models fit only at about 3-bit: DeepSeek V4.1 Flash (UD-IQ3_S, 394.5 GiB), Kimi K2.6 (IQ3_XXS, 397.3 GiB), Mistral Large 4 (UD-IQ3_XXS, 394.4 GiB).
- Raise the GPU memory limit first. macOS keeps part of unified memory away from the GPU by default. Run
sudo sysctl iogpu.wired_limit_mb=481280before you load any of these. - Prompt processing is the real limit, not memory. On the older M3 Ultra, a 16K-token prompt into GLM-5 took more than 2 minutes before the first token.
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What Fits in 512GB
Sizes from the Hugging Face API, read 1 November 2026, split files summed. 1 GiB = 1,073,741,824 bytes. Apple’s “512GB” is 512 GiB. With the limit raised to about 470 GiB, a file under about 440 GiB leaves room for the KV cache.
| Model | Params (HF count) | Quant | Size (GiB) | Fits 512GB? |
|---|---|---|---|---|
| GLM-5.3 | 753B | UD-Q4_K_XL | 435.2 | Yes, with the limit raised |
| GLM-5.3 | 753B | UD-Q6_K_XL | 637.4 | No |
| MiniMax M3 | 427B | Q8_0 | 422.5 | Yes |
| MiniMax M3 | 427B | Q6_K | 344.0 | Yes, with long context |
| DeepSeek V4.1 Flash 1017 | 763B | UD-IQ3_S | 394.5 | Yes |
| DeepSeek V4.1 Flash 1017 | 763B | UD-Q3_K_XL | 451.8 | Tight: little cache |
| DeepSeek V4.1 Flash 1017 | 763B | UD-Q4_K_XL | 466.3 | No room for cache |
| Kimi K2.6 | 1,027B | IQ3_XXS | 397.3 | Yes |
| Kimi K2.6 | 1,027B | Q3_K_M | 434.8 | Tight |
| Mistral Large 4 1T-A52B | about 1T | UD-IQ3_XXS | 394.4 | Yes |
| Mistral Large 4 1T-A52B | about 1T | UD-Q3_K_XL | 458.9 | No room for cache |
| Mistral Large 4 1T-A52B | about 1T | Q4_K_M | 591.2 | No |
A size quirk that most fit calculators miss. DeepSeek V4.1 Flash ships its experts already stored at about 4 bits. So its 4-bit and 8-bit GGUFs are almost the same size: UD-Q4_K_XL is 466.3 GiB and UD-Q8_K_XL is 473.5 GiB. “Q8 needs twice the memory” is false for this model. Neither fits with a usable cache.
Why GLM-5.3 Wins This Tier
The rule for a RAM tier is simple: run the biggest model that fits at 4-bit or better. Below 4-bit, quality drops faster than size. At 512GB, that model is GLM-5.3.
- At 128GB and 256GB it does not fit at 4-bit. 435.2 GiB is the reason this tier exists.
- The 1T models need 3-bit here. Kimi K2.6, DeepSeek V4.1 Flash and Mistral Large 4 all drop to IQ3-class files. Pick one of them only if a benchmark you trust shows it beats GLM-5.3 on your task, even at 3-bit.
- MiniMax M3 is the 8-bit pick. It is a 427B model, smaller than GLM-5.3, but at Q8_0 it keeps almost full quality. At Q6_K (344.0 GiB) it leaves room for long context.
The headroom is small. With a 470 GiB limit, GLM-5.3 at 4-bit leaves about 35 GiB for the KV cache and buffers. On the M3 Ultra test below, peak memory for GLM-5 rose from 391.8 GB at 1K context to 402.7 GB at 16K. Plan on 16K to 32K context at this quant. For long context, use MiniMax M3 at Q6_K (344.0 GiB).
Raise the GPU Memory Limit First
By default, macOS lets the GPU wire only part of unified memory. Community reports put the share near two-thirds to three-quarters; Apple does not publish the number. At three-quarters, a 512GB Mac gives the GPU about 384 GiB, and every pick on this page fails to load.
# about 470 GiB for the GPU; resets at reboot
sudo sysctl iogpu.wired_limit_mb=481280- Leave room for macOS. Do not set the limit to the full 524,288 MB.
- Make it persist by adding
iogpu.wired_limit_mb=481280to/etc/sysctl.conf. - Close other apps before you load a 400+ GiB file. Swap at this size freezes the machine.
How Fast It Runs
No one has published a measured big-model number from a 512GB M5 Ultra yet. Here is what exists. Every row is community-reported, and the numbers do not transfer between machines, runtimes or context lengths.
| Machine | Model and quant | Prompt (tok/s) | Generation (tok/s) | Source |
|---|---|---|---|---|
| M3 Ultra 512GB | GLM-5, MLX 4-bit, 1K context | 188.1 | 17.1 | omlx.ai user submission, 2026-03-15 |
| M3 Ultra 512GB | GLM-5, MLX 4-bit, 16K context | 119.7 | 12.9 | same run |
| M3 Ultra 512GB | Kimi K2.6, MLX DQ3_K_M, 1K context | 220.9 | 22.0 | omlx.ai user submission, 2026-05-19 |
| M3 Ultra 80-core | Llama 7B Q4_0 (llama-bench) | 1,471.24 | 92.14 | llama.cpp discussion #4167 |
| M5 Ultra 80-core | Llama 7B Q4_0 (llama-bench) | 4,944.66 | 179.10 | llama.cpp discussion #4167 |
Read the last two rows as a ratio. On the same 7B test, the M5 Ultra generates 1.9x and processes prompts 3.4x faster than the M3 Ultra. Its memory bandwidth is 1,228 GB/s against 800 GB/s.
Our estimate, not a measurement: GLM-5.3 at 4-bit on the M5 Ultra should generate somewhere near 1.5x to 1.9x the M3 Ultra’s GLM-5 figures. Big MoE models rarely scale as well as a 7B test, so treat the top of that range as a ceiling.
Prompt processing is the number that hurts. On the M3 Ultra run, a 16,384-token prompt at 119.7 tok/s takes about 137 seconds before the first token. An agent that re-sends a long context every turn pays that again. The M5 Ultra’s 3.4x prompt gain matters more at this tier than its generation gain. A runtime with a prefix cache, such as oMLX, avoids re-processing the same prompt.
Is 512GB Worth It Over 256GB?
| 256GB | 512GB | |
|---|---|---|
| Price (M5 Ultra, 80-core GPU, 1TB) | $10,799 | $22,299 |
| Biggest comfortable class | 120B-320B (GLM-5.3-Flash) | GLM-5.3 UD-Q4_K_XL (435.2) |
| MiniMax M3 | Q4_K_M (243.3) leaves almost no room | Q8_0 (422.5) |
| 1T-class models | No useful quant | 3-bit (394-397) |
| Memory bandwidth | 1.2 TB/s | 1.2 TB/s |
Prices as of November 2026: the 512GB figure is from MacRumors (28 October 2026), the 256GB figure from Apple’s configurator (read 27 October 2026). The 512GB machine needs the 80-core GPU chip.
The second 256GB costs $11,500 and adds no speed. Bandwidth is the same, so every model that already fits 256GB runs at the same speed on 512GB. You pay only for bigger models.
Buy 512GB if a 750B-class model at 4-bit, or a 1T model at any quant, is the reason you buy. Buy 256GB if the 120B-320B class covers your work. MacStories ran GLM-5.3-Flash in mixed 4/8-bit on a 256GB M5 Ultra for its review. See Best local LLM for the M5 Ultra 256GB for that tier.
The Non-Mac Route to 512GB
An AMD EPYC Turin server has 12 memory channels per socket and holds 512GB or more. The speed math is different:
- Bandwidth: 12 channels of DDR5-6000 give about 576 GB/s in theory, under half the M5 Ultra’s 1,228 GB/s. Fill all 12 channels to get it. Generation speed follows bandwidth.
- Prompt processing: a CPU is slower than the Ultra’s GPU. Add a GPU for the attention layers and you change the cost picture.
- Memory prices: DDR5 RDIMM prices rose sharply in 2026. Check current listings before you price a build.
The server wins on upgrades and on 1TB+ capacity. The Mac wins on bandwidth per dollar at exactly 512GB, on power and on noise. See EPYC server CPU inference for MoE models for the server build.
Sources
- Mac Studio M5 Ultra 512GB price and availability: MacRumors, 2026-10-28; 80-core base price: apple.com/shop/buy-mac/mac-studio configurator data (read 2026-11-01); bandwidth: apple.com/mac-studio/specs
- GGUF sizes, Hugging Face API (read 2026-11-01): unsloth/GLM-5.3-GGUF, bartowski/MiniMax-M3-GGUF, unsloth/DeepSeek-V4.1-Flash-1017-GGUF, bartowski/moonshotai_Kimi-K2.6-GGUF, unsloth/Mistral-Large-4-1T-A52B-GGUF, ggml-org/Mistral-Large-4-1T-A52B-GGUF
- Parameter counts: Hugging Face safetensors totals for zai-org/GLM-5.3, MiniMaxAI/MiniMax-M3, deepseek-ai/DeepSeek-V4.1-Flash-1017, moonshotai/Kimi-K2.6
- Apple Silicon llama-bench table: llama.cpp discussion #4167
- M3 Ultra 512GB runs (user-submitted, unverified by oMLX): GLM-5 MLX 4-bit, Kimi K2.6 DQ3_K_M
- GPU wired-memory limit: llama.cpp discussion #2182; MLX set_wired_limit docs
- GLM-5.3-Flash on a 256GB M5 Ultra: MacStories review
- EPYC Turin memory: Chips and Cheese, 2024-10-11
See Also
- Can I Run Kimi K3.1 Pro Locally? — why 1.56 TB does not fit even 512GB, and the 220 GB expert-streaming experiment
- Best local LLM for the M5 Ultra 256GB — the tier below, at half the price
- Best models for the biggest Mac Studio — 96GB and 256GB picks
- Which Mac Studio should you buy? — every M5 configuration
- Can I run Mistral Large 4 locally? — the 1T model in detail
- DeepSeek V4.1 Flash GSQ-RCO quants — smaller files for the same model
- Kimi K3 vs DeepSeek V4 vs GLM-5.2 — how the frontier open models compare
- Best local LLM for 128GB RAM — the tier most buyers actually need
Before you order parts, check the tested hardware list for current prices by tier.