AppleM3 UltraDesktop

Best AI Models for Mac Studio (M3 Ultra, 96GB)

Memory:96 GB Unified·Bandwidth:819.0 GB/s·GPU Cores:60 GPU cores·CPU Cores:28 CPU cores·Neural Engine:36.0 TOPS

96 GB total — ~72 GB usable as VRAM

With 96 GB of memory, this is a high-end configuration for local AI. You can comfortably run most open-source LLMs including large 70B parameter models at good quantization levels, making it one of the best setups for serious local AI work.

At this memory tier, nearly every popular open-source model is within reach. You can run Llama 3 70B at Q4_K_M or even Q5_K_M quantization with room to spare, handle coding assistants like DeepSeek Coder 33B at high quality, and easily run any 7B–30B model at full or near-full precision. Context windows remain generous even with larger models, so multi-turn conversations and long-document processing work smoothly.

Runs Well

  • 70B models (Llama 3 70B, Qwen 72B) at Q4–Q5
  • 30B models at Q6–Q8 quality
  • 7B–14B models at full FP16 precision
  • Vision models (LLaVA, CogVLM) without compromise

Challenging

  • Mixture-of-experts models like Mixtral 8x22B at higher quants
  • 120B+ models still require lower quantizations

What LLMs Can Mac Studio (M3 Ultra, 96GB) Run?

121 models · 15 good

Showing compatibility for Mac Studio (M3 Ultra, 96GB)

LLM models compatible with Mac Studio (M3 Ultra, 96GB) — ranked by performance
ModelVRAMGrade
Q4_K_M·106.4 t/s tok/s·131K ctx·EASY RUN
5.4 GBD29
Q4_K_M·66.7 t/s tok/s·EASY RUN
8.6 GBC31
Gemma 3 4B IT4.3B
Q4_K_M·201.9 t/s tok/s·EASY RUN
2.8 GBD27
Q4_K_M·94.0 t/s tok/s·8K ctx·EASY RUN
6.1 GBD29
Yi 34B Chat34.4B
Q4_K_M·26.7 t/s tok/s·4K ctx·FAIR FIT
21.4 GBB45
Q4_K_M·270.4 t/s tok/s·131K ctx·EASY RUN
2.1 GBD27
Q4_K_M·30.6 t/s tok/s·262K ctx·EASY RUN
18.7 GBC41
DeepSeek R1 0528 Qwen3 8B8.2B
Q4_K_M·103.9 t/s tok/s·131K ctx·EASY RUN
5.5 GBD29
Phi 3 Mini 4k Instruct3.8B
Q4_K_M·168.6 t/s tok/s·4K ctx·EASY RUN
3.4 GBD28
Phi 4 Mini Instruct3.8B
Q4_K_M·199.8 t/s tok/s·131K ctx·EASY RUN
2.9 GBD27
Q4_K_M·31.9 t/s tok/s·8K ctx·EASY RUN
18.0 GBC40
Q4_K_M·81.4 t/s tok/s·EASY RUN
7.0 GBC30
Q4_K_M·567.6 t/s tok/s·2K ctx·EASY RUN
1.0 GBD26
Hermes 3 Llama 3.1 8B8.0B
Q4_K_M·106.4 t/s tok/s·131K ctx·EASY RUN
5.4 GBD29
Gemma 3 1B IT1000M
Q4_K_M·868.6 t/s tok/s·33K ctx·EASY RUN
0.7 GBD26
Q4_K_M·144.8 t/s tok/s·33K ctx·EASY RUN
4.0 GBD28

Mac Studio (M3 Ultra, 96GB) Specifications

Brand
Apple
Chip
M3 Ultra
Type
Desktop
Unified Memory
96 GB
Memory Bandwidth
819.0 GB/s
GPU Cores
60
CPU Cores
28
Neural Engine
36.0 TOPS
Form Factor
Mac Studio
Memory Type
LPDDR5
NPU
32-core Neural Engine
MSRP
$3,999
Release Date
2025-03-12

Get Started

Ollama (Recommended)

$curl -fsSL https://ollama.com/install.sh | sh
$ollama run llama3:8b

LM Studio

LM Studio

Download LM Studio, search for a model, and run it with one click.

Devices to Consider

Similar devices and upgrades with more memory or higher bandwidth

Frequently Asked Questions

Can Mac Studio (M3 Ultra, 96GB) run Qwen3 Next 80B A3B Instruct?

Yes, the Mac Studio (M3 Ultra, 96GB) with 96 GB unified memory can run Qwen3 Next 80B A3B Instruct, Llama 3.3 70B Instruct, Llama 3.1 70B Instruct, and 1390 other models. 8 models achieve excellent performance, and 76 run at good quality. Apple Silicon's unified memory architecture lets the GPU access the full memory pool without copying data, making it efficient for AI workloads.

How much memory is available for AI on Mac Studio (M3 Ultra, 96GB)?

The Mac Studio (M3 Ultra, 96GB) has 96 GB unified memory. After macOS reserves ~3.5 GB for the operating system, approximately 92.5 GB is available for AI models. Unlike discrete GPUs where VRAM is separate from system RAM, Apple Silicon shares one memory pool between the CPU and GPU — this means no data copying overhead, but you share memory with macOS and open apps.

Is Mac Studio (M3 Ultra, 96GB) good for AI?

With 96 GB unified memory and 819.0 GB/s bandwidth, the Mac Studio (M3 Ultra, 96GB) is excellent for running local AI models. It supports 84 models at good quality or better. This is a premium configuration — you can run large 30B+ parameter models at good quality, and most 7B models at maximum quality. Ideal for professional AI workloads.

What's the best model for Mac Studio (M3 Ultra, 96GB)?

The top-rated models for the Mac Studio (M3 Ultra, 96GB) are Qwen3 Next 80B A3B Instruct, Llama 3.3 70B Instruct, Llama 3.1 70B Instruct. With this much memory, you can prioritize quality — use higher quantizations (Q5/Q6) for better output, or run larger 30B+ models for more capable reasoning.

How fast is Mac Studio (M3 Ultra, 96GB) for AI inference?

With 819.0 GB/s memory bandwidth, the Mac Studio (M3 Ultra, 96GB) achieves approximately 127 tok/s on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~64 tok/s. Apple Silicon achieves high efficiency (~70%) thanks to unified memory — there's no PCIe bottleneck between CPU and GPU.

tok/s = (819 GB/s ÷ model GB) × efficiency

Apple Silicon achieves ~70% bandwidth efficiency thanks to unified memory and Metal acceleration.

Estimated speed on Mac Studio (M3 Ultra, 96GB)

Real-world results typically within ±20%.

Learn more about tok/s estimation →

Can I run AI offline on Mac Studio (M3 Ultra, 96GB)?

Yes — once you download a model, it runs entirely on the Mac Studio (M3 Ultra, 96GB) without internet. Applications like Ollama and LM Studio make it straightforward to download, manage, and run models locally. All your conversations stay private on your device with zero data sent to external servers. This is one of the key advantages of local AI: complete privacy, no API costs, and no rate limits.