192GB VRAM

Mac M3 Ultra 192G — what LLMs can it run?

101 of 110 indexed models fit comfortably in 192GB at 4K context, each at the highest-quality quant that still leaves headroom.

The short answer for Mac M3 Ultra 192G

192 GB, 819 GB/s Unified LPDDR5. 101 of 110 models in this index fit comfortably at 4K context; 101 load at all.

Biggest that fits
Qwen3 235B-A22B Instruct — 119.6 GB at Q3_K_M — 24.4 GB spare at 4K, so longer context comes out of a thin margin.
Room to grow
DBRX Instruct — 84.3 GB at Q4_K_M — under 60% of the card, which leaves 59.7 GB for a long context window or a second process.
Speed ceiling
Llama 3.1 8B Instruct at Q4_K_M reads 4.6 GB of weights per token, so 819 GB/s puts a hard ceiling near 177 tok/s. That is arithmetic on two published numbers, not a benchmark — real throughput lands below it. No run on this card has been measured here, so there is nothing to compare the ceiling against.
The wall you will hit
The GPU's share of unified memory, not the 192 GB on the box. macOS reserves part of the pool for the system and caps what a single process may wire down, so the practical budget is meaningfully below nameplate — the limit is adjustable (`iogpu.wired_limit_mb`) but it is not absent. Bandwidth is 819 GB/s, which is the number that decides tok/s once a model fits.
Best local LLM for Apple silicon

70B+ · 14

Mac M3 Ultra 192G — what LLMs can it run? — 70B+
ModelQuantEst. VRAMHeadroomtok/s
Qwen3 235B-A22B Instruct235B-A22BQ3_K_M119.6 GB+24.4 GB≤81Ceiling
DBRX Instruct132B MoEQ4_K_M84.31 GB+59.7 GB≤40Ceiling
Qwen3.8-Flash-Next125B-A6BQ4_K_M79.32 GB+64.7 GB≤237Ceiling
Nemotron 3.5 Super VL 120B-A12B120B-A12BQ4_075.12 GB+68.9 GB≤121Ceiling
GPT-OSS 120B117B MoEMXFP466.4 GB+77.6 GB≤312Ceiling
Llama 4 Scout 17B (16E)109B MoEQ4_K_M69.88 GB+74.1 GB≤84Ceiling
GLM-4.5-Air106B MoEQ4_K_M67.94 GB+76.1 GB≤119Ceiling
Llama 3.2 90B Vision Instruct90BQ4_K_M57.5 GB+86.5 GB≤16Ceiling
Nemotron 3.5 Bolt 74B-A9B74B-A9BIQ2_XXS23.05 GB+121 GB≤322Ceiling
Qwen2.5 72B Instruct72BQ5_K_M55.31 GB+88.7 GB≤17Ceiling
Llama 3.1 70B Instruct70BQ5_K_M53.75 GB+90.3 GB≤17Ceiling
Llama 3.3 70B Instruct70BQ5_K_M53.75 GB+90.3 GB≤17Ceiling
DeepSeek-R1-Distill-Llama-70B70BQ4_K_M46.1 GB+97.9 GB≤20Ceiling
Jamba 1.5 Mini52B-A12BQ4_K_M33.01 GB+111 GB≤118Ceiling

32B · 30

Mac M3 Ultra 192G — what LLMs can it run? — 32B
ModelQuantEst. VRAMHeadroomtok/s
Kimi Linear 48B-A3B Instruct48B-A3BQ8_053.33 GB+90.7 GB≤270Ceiling
Mixtral 8x7B Instruct47B MoEQ4_K_M30.13 GB+113.9 GB≤110Ceiling
Seed-OSS 36B Instruct36BQ5_K_M27.81 GB+116.2 GB≤34Ceiling
Qwen3.6 35B-A3B35B-A3BQ8_039.6 GB+104.4 GB≤270Ceiling
Command R 35B35BQ4_K_M22.86 GB+121.1 GB≤41Ceiling
Yi 1.5 34B Chat34BQ4_K_M22.82 GB+121.2 GB≤41Ceiling
Qwen3 32B Instruct32BQ4_K_M21.85 GB+122.2 GB17–22Derived
Qwen2.5 32B Instruct32BQ4_K_M21.69 GB+122.3 GB17–22Derived
Qwen2.5-Coder 32B Instruct32BQ4_K_M21.69 GB+122.3 GB17–22Derived
DeepSeek-R1-Distill-Qwen-32B32BQ4_K_M21.69 GB+122.3 GB17–22Derived
Nemotron 3.5 Lightning 30B-A3B30B-A3BQ8_035.14 GB+108.9 GB≤270Ceiling
Gemma 4 31B IT31BQ8_035.72 GB+108.3 GB10–14Derived
Qwen3 30B-A3B Instruct30B-A3BQ5_K_M23.04 GB+121 GB≤405Ceiling
Qwen3-Coder 30B-A3B Instruct30B-A3BQ5_K_M23.04 GB+121 GB≤405Ceiling
Qwen3-VL 30B-A3B Instruct30B-A3BQ8_034.28 GB+109.7 GB≤271Ceiling
GLM-4.7-Flash30B-A3BQ8_033.47 GB+110.5 GB≤270Ceiling
Granite 4.2 30B30BQ8_033.61 GB+110.4 GB11–14Derived
Muse Glimmer 30B30BQ8_031.08 GB+112.9 GB11–15Derived
Qwen3.8 27B27BQ4_K_M17.47 GB+126.5 GB20–27Derived
Qwen3.6 27B27BQ8_030.71 GB+113.3 GB11–15Derived
Gemma 3 27B IT27BQ4_K_M18.37 GB+125.6 GB20–27Derived
Gemma 2 27B Instruct27BQ5_K_M21.76 GB+122.2 GB17–23Derived
Gemma 4 26B-A4B IT26B-A4BQ8_028.42 GB+115.6 GB≤203Ceiling
Mistral Small 24B Instruct24BQ4_K_M15.89 GB+128.1 GB23–30Derived
LFM2.5 24B-A2B24B-A2BQ8_026.73 GB+117.3 GB≤331Ceiling
Devstral Small 1.1 24B24BQ6_K20.91 GB+123.1 GB17–23Derived
Magistral Small 1.2 24B24BQ6_K20.91 GB+123.1 GB17–23Derived
Codestral 22B22BQ4_K_M15.03 GB+129 GB25–33Derived
ERNIE 4.5 21B-A3B21B-A3BQ8_024.44 GB+119.6 GB≤271Ceiling
GPT-OSS 20B21B MoEMXFP412.76 GB+131.2 GB≤414Ceiling

14B · 18

Mac M3 Ultra 192G — what LLMs can it run? — 14B
ModelQuantEst. VRAMHeadroomtok/s
InternLM2 20B Chat20BQ5_K_M15.59 GB+128.4 GB24–31Derived
DeepSeek-Coder-V2-Lite Instruct16B-A2.4BQ8_017.56 GB+126.4 GB≤338Ceiling
DeepSeek-V2-Lite Chat16B-A2.4BQ4_K_M10.08 GB+133.9 GB≤593Ceiling
StarCoder2 15B15BQ4_K_M10.19 GB+133.8 GB37–49Derived
Qwen3 14B Instruct14BQ5_K_M11.65 GB+132.4 GB32–42Derived
Qwen2.5 14B Instruct14BQ5_K_M11.73 GB+132.3 GB32–42Derived
DeepSeek-R1-Distill-Qwen-14B14BQ4_K_M10.14 GB+133.9 GB38–50Derived
Phi-4 14B14BQ5_K_M11.77 GB+132.2 GB32–42Derived
Phi-3 Medium 14B Instruct14BQ6_K12.86 GB+131.1 GB29–39Derived
Mistral Nemo 12B Instruct12BQ6_K11.14 GB+132.9 GB33–44Derived
Gemma 3 12B IT12BQ5_K_M9.84 GB+134.2 GB39–51Derived
Mellum2.1 12B-A2.5B Thinking12B-A2.5BQ8_013.6 GB+130.4 GB≤325Ceiling
Stable LM 2 12B Chat12BQ4_K_M8.35 GB+135.7 GB46–60Derived
Llama 3.2 11B Vision Instruct11BQ8_012.9 GB+131.1 GB29–38Derived
Solar 10.7B Instruct11BQ4_K_M7.6 GB+136.4 GB52–68Derived
Falcon 3 10B Instruct10BQ4_K_M7.28 GB+136.7 GB53–70Derived
Gemma 2 9B Instruct9BQ8_011.7 GB+132.3 GB34–45Derived
Qwen3.5 9B9BQ8_010.37 GB+133.6 GB34–45Derived

7B · 25

Mac M3 Ultra 192G — what LLMs can it run? — 7B
ModelQuantEst. VRAMHeadroomtok/s
GLM-4-9B-Chat9BQ8_010.16 GB+133.8 GB35–46Derived
Qwen3-VL 8B Instruct8BQ8_010.39 GB+133.6 GB36–47Derived
Granite 4.2 8B8BQ8_010.45 GB+133.6 GB36–47Derived
Ministral 3 8B Instruct8BQ8_010.02 GB+134 GB37–49Derived
Qwen2-VL 7B Instruct7BQ4_K_M5.49 GB+138.5 GB67–88Derived
Granite 3.1 8B Instruct8BQ4_K_M5.88 GB+138.1 GB67–89Derived
Qwen3 8B Instruct8BQ6_K7.64 GB+136.4 GB50–66Derived
Llama 3.1 8B Instruct8BQ8_09.47 GB+134.5 GB39–52Derived
Nous Hermes 3 Llama 3.1 8B8BQ4_K_M5.64 GB+138.4 GB69–91Derived
Aya 23 8B8BQ4_K_M5.64 GB+138.4 GB69–91Derived
OpenChat 3.6 8B8BQ4_K_M5.64 GB+138.4 GB69–91Derived
DeepSeek-R1-Distill-Llama-8B8BQ5_K_M6.51 GB+137.5 GB59–78Derived
InternLM2 7B Chat7BQ4_K_M5.45 GB+138.6 GB71–94Derived
Qwen2.5 7B Instruct7BQ6_K6.77 GB+137.2 GB54–71Derived
Qwen2.5-Coder 7B Instruct7BQ4_K_M5.07 GB+138.9 GB72–96Derived
DeepSeek-R1-Distill-Qwen-7B7BQ4_K_M5.07 GB+138.9 GB72–96Derived
Gemma 4 E4B ITE4BQ8_08.46 GB+135.5 GB42–55Derived
OLMo 2 7B Instruct7BQ8_010.3 GB+133.7 GB43–57Derived
OLMo 3 7B Instruct7BQ8_010.3 GB+133.7 GB43–57Derived
WizardLM-2 7B7BQ4_K_M5.14 GB+138.9 GB76–101Derived
Mistral 7B Instruct v0.37BQ6_K6.75 GB+137.3 GB56–75Derived
Zephyr 7B Beta7BQ6_K6.75 GB+137.3 GB56–75Derived
Gemma 4 E2B ITE2BQ8_05.2 GB+138.8 GB≤175Ceiling
Qwen3.5 4B4BQ8_04.97 GB+139 GB≤187Ceiling
Gemma 3 4B IT4BQ8_05.05 GB+139 GB≤189Ceiling

≤3B · 14

Mac M3 Ultra 192G — what LLMs can it run? — ≤3B
ModelQuantEst. VRAMHeadroomtok/s
Qwen3 4B Instruct4BQ6_K4.05 GB+140 GB≤263Ceiling
Phi-4 Mini Instruct3.8BQ8_04.81 GB+139.2 GB≤211Ceiling
Phi-3.5 Mini Instruct3.8BQ8_05.89 GB+138.1 GB≤212Ceiling
Granite 4.2 3B3BQ8_04.41 GB+139.6 GB≤222Ceiling
Llama 3.2 3B Instruct3BQ8_04.05 GB+140 GB≤253Ceiling
Qwen2.5 3B Instruct3BQ8_03.59 GB+140.4 GB≤263Ceiling
SmolLM3 3B3BQ8_03.73 GB+140.3 GB≤263Ceiling
Gemma 2 2B Instruct2BQ8_03.34 GB+140.7 GB≤311Ceiling
Qwen3.5 2B2BQ8_02.23 GB+141.8 GB≤414Ceiling
Qwen3 1.7B Instruct1.7BQ8_02.39 GB+141.6 GB≤471Ceiling
Qwen2.5 1.5B Instruct1.5BQ8_01.83 GB+142.2 GB≤528Ceiling
Llama 3.2 1B Instruct1BQ8_01.51 GB+142.5 GB≤655Ceiling
Qwen3.5 0.8B0.8BQ8_00.94 GB+143.1 GB≤1011Ceiling
Qwen2.5 0.5B Instruct0.5BQ8_00.6 GB+143.4 GB≤1671Ceiling

How this list is built

Each row is the lowest-perplexity-loss quant of that model whose estimated total — weights plus KV cache at 4K context plus activation buffer — uses at most 88% of the card. That is the calculator's "green" threshold, so every row here has real headroom rather than only just fitting. Raise the context length and the list shortens; the calculator lets you check any combination directly. The speed column is this card: a measured run, a range scaled from this card's own Llama 2 7B benchmark, or a bandwidth ceiling. A figure that only exists for the RTX 4090 is labelled as that card.

Measured on this card

No benchmark runs in this index were recorded on a Mac M3 Ultra 192G. Every figure on this page is calculated from the model architecture and the quant level — treat them as estimates, not measurements.

Cards with the same budget

What fits is decided by memory, so every 192GB card of this type returns the same list. These pages are not different answers — they differ in throughput, which this index does not measure per card.

Same list, different speed — play one sentence on both cards: Mac M3 Ultra 192G vs Mac M2 Ultra 192G (Qwen3 32B Instruct)

Setup guides for this card

Step-by-step guides written for the Mac M3 Ultra 192G's runtime or memory size, with the commands and the checks that prove the model is running on the card.

Stepping up

A Mac M5 Ultra 512G (512GB) fits 4 more of the indexed models than this card. Mac M5 Ultra 512G →

Common questions

What is the best local LLM for a Mac M3 Ultra 192G?

For everyday use, DBRX Instruct at Q4_K_M — about 84.3 GB of the card's 192 GB at 4K context, leaving 59.7 GB for a longer window. If you want the largest thing that will load, that is Qwen3 235B-A22B Instruct at Q3_K_M (119.6 GB, 24.4 GB spare). "Best" here means best fit for the memory budget — this index does not run task benchmarks, so it cannot tell you which model is smarter.

Can a Mac M3 Ultra 192G run Llama 4 Maverick 17B (128E)?

No. Its smallest build here, Q3_K_M, needs about 203.0 GB and this card has 144.0 GB usable — short by 59.0 GB before any context beyond 4K. The largest model this card does clear is Qwen3 235B-A22B Instruct.

How many tokens per second does a Mac M3 Ultra 192G do on an 8B model at Q4?

This index has no measured run on this card, so it does not publish a figure. What can be stated from specifications: generating a token requires reading every weight once, Llama 3.1 8B Instruct at Q4_K_M is 4.6 GB of weights, and this card moves 819 GB/s — a ceiling near 177 tok/s. Batch size, context length, the runtime and how much of the model sits in cache all take you below it.

Mac M3 Ultra 192G or Mac M2 Ultra 192G for local LLMs?

They hold the same models: 192 GB against 192 GB fits 101 and 101 of 110 respectively at 4K. The difference is throughput — 819 GB/s against 800 GB/s, a 1.0× gap in how fast the weights can be read, which is what token generation is bound by. The Mac M3 Ultra 192G generates faster on any model both can hold.

101 of 110 indexed models fit comfortably in 192GB at 4K context, each at the highest-quality quant that still leaves headroom.

This page's figures change when the model or the runtime does.Last updated 2026-10-18 RSS → /feed.xml