NVIDIA RTX 5090 vs Apple M3 Ultra (96GB)
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 99 open-weight models.
Quick verdict
Apple M3 Ultra (96GB) wins for local AI inference. It has 64 GB more VRAM and -54.3% more memory bandwidth, runs 69 models natively (vs 54), and exclusively fits 15 models the other cannot. Note: NVIDIA RTX 5090 uses CUDA while Apple M3 Ultra (96GB) uses METAL; software ecosystem matters for your framework.
Specs comparison
| Spec | NVIDIA RTX 5090 | Apple M3 Ultra (96GB) |
|---|---|---|
| VRAM | 32 GB | 96 GB unified |
| Memory type | GDDR7 | LPDDR5X |
| Bandwidth | 1792 GB/s(+119%) | 819 GB/s |
| CPU cores | N/A | 28 (20P + 8E) |
| Architecture | Blackwell | Apple M3 Ultra |
| Backend | CUDA | METAL |
| Tier | Consumer | Workstation |
| Released | 2025 | 2025 |
| Models (native) | 54 | 69 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 5090 | Apple M3 Ultra (96GB) | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | N/A | 8.5 t/s(Q8_0) | N/A |
| Qwen 3.6 27B(27B) | 83 t/s(NVFP4) | 12 t/s(BF16) | +592% |
| Llama 3.1 8B Instruct(8B) | 68.2 t/s(BF16) | 38.4 t/s(BF16) | +78% |
| Qwen 2.5 7B Instruct(7.6B) | 74.3 t/s(BF16) | 41.8 t/s(BF16) | +78% |
Delta is NVIDIA RTX 5090 relative to Apple M3 Ultra (96GB).
Only NVIDIA RTX 5090 can run(0)
No exclusive models: Apple M3 Ultra (96GB) can run everything NVIDIA RTX 5090 can.
Only Apple M3 Ultra (96GB) can run(15)
- Step 3.7 Flash198B
- Step 3.5 Flash196.81B
- Qwen3.8-Flash-Next180B
- Mixtral 8x22B Instruct v0.1141B
- Mistral Medium 3.5 128B128B
- Qwen 3.5 122B-A10B (MoE)122B
- Nemotron 3 Super 120B120B
- GPT-OSS 120B117B
- Llama 4 Scout 109B109B
- GLM-4.5 Air 106B106B
- GLM-4.6V 106B106B
- Qwen 2.5 72B Instruct72B
- +3 more
Both run natively(54)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Mixtral 8x7B Instruct v0.151.6 t/svs14 t/s
- Command-R 35B48.4 t/svs13.7 t/s
- Qwen 3.5 35B-A3B (MoE)225.4 t/svs32.5 t/s
- Qwen 3.6 35B59.3 t/svs9.1 t/s
- Ornith 1.5 35B-A3B (MoE)225.4 t/svs32.5 t/s
- Yi 1.5 34B Chat60.6 t/svs9.3 t/s
- Qwen3 32B65.7 t/svs9.8 t/s
- Qwen 2.5 32B Instruct63.3 t/svs9.8 t/s
- Qwen 2.5 Coder 32B Instruct63.3 t/svs9.8 t/s
- DeepSeek R1 Distill Qwen 32B63.3 t/svs9.8 t/s
- Nemotron 3 Nano 30B214.3 t/svs32.1 t/s
- Gemma 4 31B69.1 t/svs10.4 t/s
- Qwen3 30B-A3B (MoE)200.6 t/svs31.5 t/s
- Nemotron 3.5 Lightning 30B-A3B230.6 t/svs32.7 t/s
- Muse Glimmer 30B82.7 t/svs11.7 t/s
- Gemma 2 27B Instruct69.8 t/svs11.4 t/s
- +38 more on both
Which should you choose?
Choose NVIDIA RTX 5090 if:
- • Faster token generation is the priority
- • You rely on CUDA-based tools (PyTorch, vLLM, Ollama)
Choose Apple M3 Ultra (96GB) if:
- • You need to run larger models (>32 GB VRAM)
- • You're on macOS and want native Metal acceleration (MLX, llama.cpp)
- • Unified memory matters (CPU/GPU share the same pool, no data copy overhead)
Frequently asked questions
- Which is better for local AI, the NVIDIA RTX 5090 or Apple M3 Ultra (96GB)?
- For local AI inference, the Apple M3 Ultra (96GB) has the edge. It offers 96 GB VRAM (vs 32 GB) and 819 GB/s bandwidth (vs 1792 GB/s), letting it run 69 models natively in VRAM vs 54 for its rival.
- How much VRAM does the NVIDIA RTX 5090 have vs the Apple M3 Ultra (96GB)?
- The NVIDIA RTX 5090 has 32 GB of GDDR7 at 1792 GB/s. The Apple M3 Ultra (96GB) has 96 GB of LPDDR5X at 819 GB/s. The Apple M3 Ultra (96GB) has 64 GB more VRAM, allowing it to run 15 models the NVIDIA RTX 5090 cannot fit natively.
- Can the NVIDIA RTX 5090 run Llama 3.3 70B?
- The NVIDIA RTX 5090 can run Llama 3.3 70B with CPU offload at NVFP4, but at reduced speed.
- 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 RTX 5090 and Apple M3 Ultra (96GB) for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA RTX 5090 has 32 GB VRAM at 1792 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 RTX 5090 runs 54 models natively vs 69 for the Apple M3 Ultra (96GB).