397BTier 100Needs ~254.9 GB
Apple
Operating mode
Apple Silicon can fit a lot thanks to unified memory. This selector changes which serving posture we optimize for when surfacing the best local LLMs for this Mac.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Apple Silicon local AI performance. Excellent for local AI. Your Mac Studio M3 Ultra 96GB with 96 GB unified memory can run 134 models natively, 195 more with limits. The best match is Qwen 3.6 35B A3B at 71 tok/s for interactive local LLM use.
134
Run great
329
Total compatible
111B
Max parameters
71
Best tok/sEST.
Comparison guide
Top models ranked for coding, chat, and writing with FAQ and buyer guidance — the comparison-intent companion to this spec sheet.
Quick picks
Top recommendations for common local AI workloads on your Mac Studio M3 Ultra 96GB
Mac Studio M3 Ultra 96GB with 96 GB unified memory. Third-generation Apple Silicon built on 3nm process with dynamic caching GPU architecture, significantly improving AI inference efficiency.
All 374 models tested
Every model ranked by how well it runs on your Mac Studio M3 Ultra 96GB, grouped by fit quality
These models fit comfortably and run at full speed on your Mac.
These models run but may need quantization or have reduced context windows.
These models are too large for your Mac's unified memory.
Beyond LLMs
What AI tasks this Mac can handle — from text generation to image and video creation.
| Capability | Status | Representative Model |
|---|---|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 |
| LLM Coding (30B) | Runs natively | Qwen 3 30B Q4 |
| LLM Large (70B) |
Same chip, more memory
Compare M3 configurations to see which models become available
18 GB unified memory
59
Run great
231
Total fit
Architecture
Apple M3 is built on TSMC's 3nm process, the first consumer chips at this node. It introduces Dynamic Caching for more efficient GPU memory allocation and hardware-accelerated ray tracing.
AI Relevance
Dynamic Caching improves GPU utilization for compute workloads including ML inference. The M3 Ultra with up to 512 GB unified memory can theoretically hold even unquantized 70B models, though memory bandwidth remains the throughput bottleneck.
M3's dynamic caching GPU architecture allocates local memory in hardware in real-time, improving GPU utilization for AI workloads. The M3 Max reaches 400 GB/s bandwidth, competitive with mid-range discrete GPUs.
All workloads
The best local LLM for each task on your Mac Studio M3 Ultra 96GB
Chat
SQwen 3.5 27B matches Chat and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Coding
SQwen3-Coder-Next is a specialized fit for Coding. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Agentic Coding
SQwen3-Coder-Next is a specialized fit for Agentic Coding. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Just out of reach
High-quality models that need a bit more memory
Image & Video Generation
51 of 52 models can generate images or video on your Mac Studio M3 Ultra 96GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~4.6s | S |
| Stable Diffusion 1.5Image | 512×768 | ~9.2s | S |
| Realistic Vision v5.1Image | 512×768 | ~9.2s | S |
| DreamShaper 8Image | 512×768 | ~9.2s | S |
| LCM DreamShaper v7 |
Get started in 2 minutes
Everything you need to start running models locally with Metal acceleration and Apple Silicon unified memory
Ollama runs natively on macOS with Metal GPU acceleration. One command to install.
curl -fsSL https://ollama.com/install.sh | shQwen 3.6 35B A3B is the best match for your Mac Studio M3 Ultra 96GB. Pull and run it:
ollama run qwen:3.6:35b:a3bUpgrade paths
See what you unlock with more unified memory
Upgrade options
NVIDIA A100 80GBNext step upUnlocks 6 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 51%.
~$15,000 MSRP
Unlocks 7 additional models that do not fit on the current setup.
~$2,499 MSRP
Unlocks 7 additional models that do not fit on the current setup.
~$4,999 MSRP
Unlocks 20 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 142%.
~$8,000 MSRP
Yes! Mac Studio M3 Ultra 96GB (96 GB unified memory) can run 134 models at full speed and 329 total. Top picks: Qwen 3.6 35B A3B (score: 95/100), Qwen3-Coder 30B A3B Instruct (score: 94/100), Qwen3-VL 30B A3B Instruct (score: 94/100). See the full tiered compatibility list above.
Mac Studio M3 Ultra 96GB has 96 GB of unified memory shared between CPU and GPU, all available for AI model inference. Unlike discrete GPUs with separate VRAM, unified memory means models can use the full 96 GB without data transfer overhead.
Not exactly. Unified memory is excellent for making larger models fit on Apple Silicon, because the CPU and GPU share one memory pool. But it is still not identical to dedicated VRAM on a high-bandwidth discrete GPU. For local AI, unified memory often wins on flexibility and capacity, while discrete GPUs can still win on raw tokens per second once a model fits comfortably.
Compare with similar
Related guides
| Runs natively |
| Llama 3.1 70B Q4 |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 |
| Image Gen (Flux) | Runs natively | Flux.1 Dev FP16 |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 |
| Video Short (25f) | Runs natively | LTX Video 2B |
| Video Long (100f) | Runs with sequential offload | Wan Video 14B |
| 512×768 |
| ~2.7s |
| S |
| PixArt-SigmaImage | 1024×1024 | ~36.7s | S |
| FramePack I2VVideo | 1280×720 | ~1m 7s/frame | S |
| SDXL TurboImage | 512×512 | ~4.6s | S |
| SDXL LightningImage | 1024×1024 | ~13.7s | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | ~36.7s | S |
| Playground v2.5Image | 1024×1024 | ~55s | S |
| RealVisXL v5.0Image | 1024×1024 | ~41.2s | S |
| DreamShaper XLImage | 1024×1024 | ~41.2s | S |
| Juggernaut XL v9Image | 1024×1024 | ~41.2s | S |
| Animagine XL 3.1Image | 1024×1024 | ~41.2s | S |
| Pony Diffusion V6 XLImage | 1024×1024 | ~41.2s | S |
| Animagine XL 4.0Image | 1024×1024 | ~41.2s | S |
| Illustrious XLImage | 1024×1024 | ~41.2s | S |
| Wan Video 2.1 1.3BVideo | 480×832 | ~26.8s/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | ~1m 4s | S |
| Flux.2 Klein 4BImage | 1024×1024 | ~11s | S |
| LTX Video 2BVideo | 1280×720 | ~31.8s/frame | S |
| KolorsImage | 1024×1024 | ~1m 13s | S |
| Stable CascadeImage | 1024×1024 | ~1m 32s | S |
| AuraFlow v0.3Image | 1536×1536 | ~2m 45s | S |
| Stable Diffusion 3.5 LargeImage | 1024×1024 | ~3m 22s | S |
| Stable Diffusion 3.5 Large TurboImage | 1024×1024 | ~36.7s | S |
| CogVideoX 2BVideo | 720×480 | ~31.8s/frame | S |
| HunyuanVideoVideo | 720×1280 | ~1m 7s/frame | S |
| ChromaImage | 1024×1024 | ~36.7s | S |
| Z-Image TurboImage | 1536×1536 | ~37.8s | S |
| Flux.1 DevImage | 1024×1024 | ~2m 45s | S |
| Flux.1 SchnellImage | 1024×1024 | ~32.1s | S |
| LTX Video 13BVideo | 1280×720 | ~1m 7s/frame | S |
| Flux.1 Kontext DevImage | 1024×1024 | ~3m 3s | S |
| AnimateDiff v1.5.3Video | 512×768 | ~16.7s/frame | S |
| Cosmos Diffusion 7BVideo | 1024×576 | ~52.5s/frame | S |
| CogVideoX 5BVideo | 720×480 | ~45.9s/frame | S |
| Wan2.2 TI2V 5BVideo | 832×480 | ~45.9s/frame | S |
| Flux.2 Klein 9BImage | 1024×1024 | ~18.3s | S |
| Flux.1 Fill DevImage | 1024×1024 | ~2m 36s | S |
| Mochi 1 PreviewVideo | 848×480 | ~1m 1s/frame | S |
| HunyuanVideo 1.5Video | 720×1280 | ~56.2s/frame | S |
| Helios 14BVideo | 1280×720 | ~1m 9s/frame | S |
| SkyReels V2 14BVideo | 1280×720 | ~1m 9s/frame | S |
| Wan Video 2.1 14BVideo | 720×1280 | ~1m 9s/frame | A |
| Wan Video 2.2 14BVideo | 720×1280 | ~1m 9s/frame | A |
| Qwen ImageImage | 1024×1024 | ~1m 2s | A |
| Qwen Image EditImage | 1024×1024 | ~1m 2s | A |
| Flux.2 DevImage | 256×256 | ~46m 4s | B |
| MAGI-1Video | 848×480 | ~1m 26s/frame | B |
| HunyuanImage 3.0Image | 256×256 | ~1m 49s | F |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
Yes, Mac Studio M3 Ultra 96GB is excellent for running LLMs locally. With 96 GB unified memory and Metal acceleration, it handles 329 models with top scores above 80/100.
Because fit and speed are not the same thing. Mac Studio M3 Ultra 96GB can often fit larger models thanks to unified memory, but a smaller NVIDIA GPU with fast dedicated VRAM and mature CUDA kernels can still deliver higher decode throughput once the model fits. In practice, Apple Silicon is excellent for flexible local AI on one machine, while CUDA often stays ahead for the easiest setup and highest raw inference speed.
We recommend using llama.cpp on Mac Studio M3 Ultra 96GB. Install it with a single command, then pull your preferred model. llama.cpp supports Metal acceleration out of the box on Apple Silicon.
For coding on Mac Studio M3 Ultra 96GB, we recommend Qwen3-Coder-Next. It achieves 37.6 tokens per second with 99K context window using 61.5 GB of unified memory. Qwen3-Coder-Next is a specialized fit for Coding. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Yes, Mac Studio M3 Ultra 96GB with 96 GB unified memory can run Flux.1 Dev at FP16. Use ComfyUI or Draw Things for the best experience on macOS.
Mac Studio M3 Ultra 96GB (96 GB unified memory) supports various AI generation tasks. For image generation, SDXL and Stable Diffusion 3.5 run well with Metal acceleration. Flux.1 Dev also runs natively. For video, LTX Video 2.3 can generate short clips.
Mac Studio M3 Ultra 96GB is excellent for AI image generation. With 96 GB unified memory and Metal GPU acceleration, it runs all major diffusion models including Flux.1, SDXL, and SD 3.5.
There are 4 upgrade path(s) from Mac Studio M3 Ultra 96GB: NVIDIA A100 80GB (80 GB), MacBook Pro M3 Max 128GB (128 GB). Upgrading would unlock larger models like Qwen 3.5 397B A17B and Devstral 2 123B Instruct and faster inference.
Yes, Mac Studio M3 Ultra 96GB with 96 GB can run Qwen 3.5 27B at near-lossless Q8 quantization and the 35B-A3B MoE variant comfortably at Q4. For maximum quality, the 27B dense model at Q8 is the best choice. Both MLX and Ollama (llama.cpp) support Qwen 3.5 on Mac.
The best local LLMs for Mac Studio M3 Ultra 96GB (96 GB) are: Qwen 3.6 35B A3B (95/100, 71 tok/s), Qwen3-Coder 30B A3B Instruct (94/100, 84 tok/s), Qwen3-VL 30B A3B Instruct (94/100, 87 tok/s). These models fit natively in unified memory with room for context. For coding, try the top coding pick above. For general chat, the highest-scored model gives the best Apple Silicon local AI experience.
Mac Studio M3 Ultra 96GB achieves 50-71 tok/s for well-fitted models with 819 GB/s memory bandwidth. Token generation speed on Apple Silicon is primarily limited by memory bandwidth and fit. Comfortable reading speed is about 6-8 tokens per second, so most natively-fitting models will feel responsive for interactive chat. MLX generally delivers 10-20% better performance than llama.cpp on newer Apple Silicon chips.