NVIDIA DGX Spark (128GB) vs Apple M3 Ultra (96GB)
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 110 open-weight models.
Quick verdict
NVIDIA DGX Spark (128GB) wins for local AI inference. It has 32 GB more VRAM and -66.7% more memory bandwidth, runs 81 models natively (vs 77), and exclusively fits 4 models the other cannot. Note: NVIDIA DGX Spark (128GB) uses CUDA while Apple M3 Ultra (96GB) uses METAL; software ecosystem matters for your framework.
Specs comparison
| Spec | NVIDIA DGX Spark (128GB) | Apple M3 Ultra (96GB) |
|---|---|---|
| VRAM | 128 GB unified | 96 GB unified |
| Memory type | LPDDR5X | LPDDR5X |
| Bandwidth | 273 GB/s | 819 GB/s(+200%) |
| CPU cores | 20 (10 Cortex-X925 + 10 Cortex-A725) | 28 (20P + 8E) |
| Architecture | Grace Blackwell | Apple M3 Ultra |
| Backend | CUDA | METAL |
| Tier | Workstation | Workstation |
| Released | 2025 | 2025 |
| Models (native) | 81 | 77 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA DGX Spark (128GB) | Apple M3 Ultra (96GB) | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | 6.2 t/s(NVFP4) | 8.5 t/s(Q8_0) | -64%at Q8_0 |
| Qwen 3.6 27B(27B) | 4.3 t/s(BF16) | 12 t/s(BF16) | -64% |
| Llama 3.1 8B Instruct(8B) | 13.7 t/s(BF16) | 38.4 t/s(BF16) | -64% |
| Qwen 2.5 7B Instruct(7.6B) | 14.9 t/s(BF16) | 41.8 t/s(BF16) | -64% |
Delta is NVIDIA DGX Spark (128GB) relative to Apple M3 Ultra (96GB), compared at the highest quantization that fits natively on both cards.
Only NVIDIA DGX Spark (128GB) can run(4)
Only Apple M3 Ultra (96GB) can run(0)
No exclusive models: NVIDIA DGX Spark (128GB) can run everything Apple M3 Ultra (96GB) can.
Both run natively(77)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Step 3.7 Flash30.4 t/svs53.8 t/s
- Step 3.5 Flash30.4 t/svs53.8 t/s
- Qwen3.8-Flash-Next57.9 t/svs69.7 t/s
- Mixtral 8x22B Instruct v0.110.7 t/svs22.8 t/s
- Mistral Medium 3.5 128B3.5 t/svs10.2 t/s
- Ornith 1.5 122B (MoE)32.6 t/svs49.6 t/s
- Qwen 3.5 122B-A10B (MoE)39.1 t/svs49.6 t/s
- Nemotron 3 Super 120B24.4 t/svs33.6 t/s
- Nemotron 3.5 Super VL 120B-A12B25.8 t/svs32.7 t/s
- GPT-OSS 120B64.2 t/svs76.2 t/s
- Llama 4 Scout 109B18.8 t/svs26.7 t/s
- GLM-4.5 Air 106B28.4 t/svs39.2 t/s
- GLM-4.6V 106B28.4 t/svs39.2 t/s
- Qwen 2.5 72B Instruct6 t/svs10.6 t/s
- Llama 3.3 70B Instruct6.2 t/svs8.5 t/s
- DeepSeek R1 Distill Llama 70B6.2 t/svs8.5 t/s
- +61 more on both
Which should you choose?
- • You need to run larger models (>96 GB VRAM)
- • You rely on CUDA-based tools (PyTorch, vLLM, Ollama)
- • Faster token generation is the priority
- • You're on macOS and want native Metal acceleration (MLX, llama.cpp)
Frequently asked questions
- Which is better for local AI, the NVIDIA DGX Spark (128GB) or Apple M3 Ultra (96GB)?
- For local AI inference, the NVIDIA DGX Spark (128GB) has the edge. It offers 128 GB VRAM (vs 96 GB) and 273 GB/s bandwidth (vs 819 GB/s), letting it run 81 models natively in VRAM vs 77 for its rival.
- How much VRAM does the NVIDIA DGX Spark (128GB) have vs the Apple M3 Ultra (96GB)?
- The NVIDIA DGX Spark (128GB) has 128 GB of LPDDR5X at 273 GB/s. The Apple M3 Ultra (96GB) has 96 GB of LPDDR5X at 819 GB/s. The NVIDIA DGX Spark (128GB) has 32 GB more VRAM, allowing it to run 4 models the Apple M3 Ultra (96GB) cannot fit natively.
- Can the NVIDIA DGX Spark (128GB) run Llama 3.3 70B?
- Yes. The NVIDIA DGX Spark (128GB) runs Llama 3.3 70B natively at NVFP4 quantization at approximately 6.2 tokens per second.
- Can the Apple M3 Ultra (96GB) run Llama 3.3 70B?
- Yes. The Apple M3 Ultra (96GB) runs Llama 3.3 70B natively at Q8_0 quantization at approximately 8.5 tokens per second.
- What is the difference between the NVIDIA DGX Spark (128GB) and Apple M3 Ultra (96GB) for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA DGX Spark (128GB) has 128 GB VRAM at 273 GB/s (CUDA backend). The Apple M3 Ultra (96GB) has 96 GB VRAM at 819 GB/s (METAL backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA DGX Spark (128GB) runs 81 models natively vs 77 for the Apple M3 Ultra (96GB).