NVIDIA RTX 5090 vs Apple M4 Max (128GB)
Side-by-side local AI comparison — VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 70 open-weight models.
Quick verdict
Apple M4 Max (128GB) wins for local AI inference. It has 96 GB more VRAM and -70% more memory bandwidth, runs 58 models natively (vs 47), and exclusively fits 11 models the other cannot. Note: NVIDIA RTX 5090 uses CUDA while Apple M4 Max (128GB) uses METAL — software ecosystem matters for your framework.
Specs comparison
| Spec | NVIDIA RTX 5090 | Apple M4 Max (128GB) |
|---|---|---|
| VRAM | 32 GB | 128 GB unified |
| Memory type | GDDR7 | LPDDR5X |
| Bandwidth | 1792 GB/s(+228%) | 546 GB/s |
| CPU cores | — | 16 (12P + 4E) |
| Architecture | Blackwell | Apple M4 Max |
| Backend | CUDA | METAL |
| Tier | Consumer | Laptop |
| Released | 2025 | 2024 |
| Models (native) | 47 | 58 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 5090 | Apple M4 Max (128GB) | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | 77.8 t/s(Q2_K) | 7.8 t/s(Q8_0) | +897% |
| Qwen 3.6 27B(27B) | 132.7 t/s(NVFP4) | 5.1 t/s(FP32) | +2502% |
| Llama 3.1 8B Instruct(8B) | 112 t/s(BF16) | 17.1 t/s(FP32) | +555% |
| Qwen 2.5 7B Instruct(7.6B) | 117.9 t/s(BF16) | 18 t/s(FP32) | +555% |
Delta is NVIDIA RTX 5090 relative to Apple M4 Max (128GB).
Only NVIDIA RTX 5090 can run(0)
No exclusive models — Apple M4 Max (128GB) can run everything NVIDIA RTX 5090 can.
Only Apple M4 Max (128GB) can run(11)
Both run natively(47)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 2.5 72B Instruct75.7 t/svs7.6 t/s
- Llama 3.3 70B Instruct77.8 t/svs7.8 t/s
- DeepSeek R1 Distill Llama 70B77.8 t/svs7.8 t/s
- Llama 3.1 70B Instruct77.8 t/svs7.8 t/s
- Mixtral 8x7B Instruct v0.1305.6 t/svs23.3 t/s
- Command-R 35B119.1 t/svs7.8 t/s
- Qwen 3.5 35B-A3B (MoE)1314.1 t/svs100.1 t/s
- Qwen 3.6 35B102.4 t/svs7.8 t/s
- Yi 1.5 34B Chat104.2 t/svs7.9 t/s
- Qwen3 32B109.3 t/svs8.3 t/s
- Qwen 2.5 32B Instruct110.3 t/svs8.4 t/s
- Qwen 2.5 Coder 32B Instruct110.3 t/svs8.4 t/s
- DeepSeek R1 Distill Qwen 32B110.3 t/svs8.4 t/s
- Nemotron 3 Nano 30B1314.1 t/svs100.1 t/s
- Gemma 4 31B115.6 t/svs8.8 t/s
- Qwen3 30B-A3B (MoE)1314.1 t/svs100.1 t/s
- +31 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)
- • You want the newer architecture and longer driver support lifecycle
Choose Apple M4 Max (128GB) 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 M4 Max (128GB)?
- For local AI inference, the Apple M4 Max (128GB) has the edge. It offers 128 GB VRAM (vs 32 GB) and 546 GB/s bandwidth (vs 1792 GB/s), letting it run 58 models natively in VRAM vs 47 for its rival.
- How much VRAM does the NVIDIA RTX 5090 have vs the Apple M4 Max (128GB)?
- The NVIDIA RTX 5090 has 32 GB of GDDR7 at 1792 GB/s. The Apple M4 Max (128GB) has 128 GB of LPDDR5X at 546 GB/s. The Apple M4 Max (128GB) has 96 GB more VRAM, allowing it to run 11 models the NVIDIA RTX 5090 cannot fit natively.
- Can the NVIDIA RTX 5090 run Llama 3.3 70B?
- Yes. The NVIDIA RTX 5090 runs Llama 3.3 70B natively at Q2_K quantization at approximately 77.8 tokens per second.
- Can the Apple M4 Max (128GB) run Llama 3.3 70B?
- Yes. The Apple M4 Max (128GB) runs Llama 3.3 70B natively at Q8_0 quantization at approximately 7.8 tokens per second.
- What is the difference between the NVIDIA RTX 5090 and Apple M4 Max (128GB) 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 M4 Max (128GB) has 128 GB VRAM at 546 GB/s (METAL backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA RTX 5090 runs 47 models natively vs 58 for the Apple M4 Max (128GB).