Best AI Models for Mac Studio (M3 Ultra, 512GB)
512 GB total — ~384 GB usable as VRAM
With 512 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, 512GB) Run?
327 models · 182 excellent · 84 good
Showing compatibility for Mac Studio (M3 Ultra, 512GB)
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
Q4_K_M·139.2 t/s tok/s·8K ctx·RUNS GREAT | Q4_K_M | 4.1 GB | 139.2 t/s | 8K | RUNS GREAT | S96 |
Q4_K_M·66.7 t/s tok/s·RUNS GREAT | Q4_K_M | 8.6 GB | 66.7 t/s | — | RUNS GREAT | S85 |
Q4_K_M·95.4 t/s tok/s·33K ctx·RUNS GREAT | Q4_K_M | 6.0 GB | 95.4 t/s | 33K | RUNS GREAT | S90 |
Q4_K_M·49.6 t/s tok/s·33K ctx·RUNS WELL | Q4_K_M | 28.6 GB | 49.6 t/s | 33K | RUNS WELL | A79 |
IQ2_M·31.5 t/s tok/s·131K ctx·DECENT | IQ2_M | 350.3 GB | 31.5 t/s | 131K | DECENT | B56 |
Q4_K_M·37.9 t/s tok/s·131K ctx·RUNS WELL | Q4_K_M | 15.1 GB | 37.9 t/s | 131K | RUNS WELL | A74 |
Q4_K_M·868.6 t/s tok/s·33K ctx·RUNS GREAT | Q4_K_M | 0.7 GB | 868.6 t/s | 33K | RUNS GREAT | S100 |
Q4_K_M·28.2 t/s tok/s·33K ctx·RUNS WELL | Q4_K_M | 20.3 GB | 28.2 t/s | 33K | RUNS WELL | A69 |
Q4_K_M·331.4 t/s tok/s·8K ctx·RUNS GREAT | Q4_K_M | 1.7 GB | 331.4 t/s | 8K | RUNS GREAT | S100 |
Q4_K_M·54.7 t/s tok/s·33K ctx·RUNS WELL | Q4_K_M | 10.5 GB | 54.7 t/s | 33K | RUNS WELL | A81 |
Q4_K_M·63.0 t/s tok/s·131K ctx·RUNS WELL | Q4_K_M | 9.1 GB | 63.0 t/s | 131K | RUNS WELL | A84 |
Q4_K_M·8.5 t/s tok/s·33K ctx·DECENT | Q4_K_M | 67.7 GB | 8.5 t/s | 33K | DECENT | B46 |
Q4_K_M·19.0 t/s tok/s·66K ctx·DECENT | Q4_K_M | 85.1 GB | 19.0 t/s | 66K | DECENT | B59 |
Q3_K_M·21.4 t/s tok/s·164K ctx·DECENT | Q3_K_M | 337.6 GB | 21.4 t/s | 164K | DECENT | B51 |
Q4_K_M·112.4 t/s tok/s·33K ctx·RUNS GREAT | Q4_K_M | 5.1 GB | 112.4 t/s | 33K | RUNS GREAT | S94 |
Q4_K_M·66.7 t/s tok/s·RUNS GREAT | Q4_K_M | 8.6 GB | 66.7 t/s | — | RUNS GREAT | S85 |
Mac Studio (M3 Ultra, 512GB) Specifications
- Brand
- Apple
- Chip
- M3 Ultra
- Type
- Desktop
- Unified Memory
- 512 GB
- Memory Bandwidth
- 819.0 GB/s
- GPU Cores
- 80
- CPU Cores
- 32
- Neural Engine
- 36.0 TOPS
- Form Factor
- Mac Studio
- Memory Type
- LPDDR5
- NPU
- 32-core Neural Engine
- Interconnect
- UltraFusion (two M3 Max dies, 10000+ connections, 2.5TB/s)
- MSRP
- $9,499
- Release Date
- 2025-03-12
Get Started
Prompt Processing
Estimated for Ornith 1.0 397B, the compute-bound phase that reads your prompt before the first reply token appears.
Short chat
1.4 s
512 tok prompt
Long chat
11.1 s
4,096 tok prompt
Document / codebase
89 s
32,768 tok prompt
Prefill is compute-bound and a different number from the decode tok/s shown elsewhere on this page — how prompt processing works →
Performance figures are estimates calibrated as of 2026-09-21 — see calibration basis →
Devices to Consider
Similar devices and upgrades with more memory or higher bandwidth
Frequently Asked Questions
- Can Mac Studio (M3 Ultra, 512GB) run GLM 5.3 Flash?
Yes, the Mac Studio (M3 Ultra, 512GB) with 512 GB unified memory can run GLM 5.3 Flash, DeepSeek V4 Flash, Hy3, and 2724 other models. 1819 models achieve excellent performance, and 577 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, 512GB)?
The Mac Studio (M3 Ultra, 512GB) has 512 GB unified memory. After macOS reserves ~3.5 GB for the operating system, approximately 508.5 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, 512GB) good for AI?
With 512 GB unified memory and 819.0 GB/s bandwidth, the Mac Studio (M3 Ultra, 512GB) is excellent for running local AI models. It supports 2396 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, 512GB)?
The top-rated models for the Mac Studio (M3 Ultra, 512GB) are GLM 5.3 Flash, DeepSeek V4 Flash, Hy3. 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, 512GB) for AI inference?
With 819.0 GB/s memory bandwidth, the Mac Studio (M3 Ultra, 512GB) 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, 512GB)
~35 tok/s~43 tok/s~26 tok/s~97 tok/sReal-world results typically within ±20%.
- Can I run AI offline on Mac Studio (M3 Ultra, 512GB)?
Yes — once you download a model, it runs entirely on the Mac Studio (M3 Ultra, 512GB) 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.